Compositions and methods for aptamer screening

ABSTRACT

Methods are provided for selecting aptamers that are specific to a target of interest from amongst a library of potential aptamer sequences. Aptamers disclosed can be used to detect and/or characterize biological entities of interest, e.g. microvesicles and/or surface antigens. Further disclosed are biomarkers that can be used for diagnosing different disorders including different types of cancer.

CROSS REFERENCE

This application claims the benefit of U.S. Provisional Patent Application Nos. 61/739,558, filed Dec. 19, 2012; which application is incorporated herein by reference in its entirety.

SEQUENCE LISTING SUBMITTED VIA EFS-WEB

The entire content of the following electronic submission of the sequence listing via the USPTO EFS-WEB server, as authorized and set forth in MPEP §1730 II.B.2(a), is incorporated herein by reference in its entirety for all purposes. The sequence listing is within the electronically filed text file that is identified as follows:

File Name: 37901815601SeqList.txt

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BACKGROUND OF THE INVENTION

The invention relates generally to the field of aptamers capable of binding to biomarkers such as microvesicle surface antigens, which are useful as therapeutics in and diagnostics of cancer and/or other diseases or disorders in which microvesicles implicated. The invention further relates to materials and methods for the administration of aptamers capable of binding to microvesicles. The microvesicles may be derived from cells indicative of cancer.

Aptamers are nucleic acid molecules having specific binding affinity to molecules through interactions other than classic Watson-Crick base pairing.

Aptamers, like peptides generated by phage display or monoclonal antibodies (“mAbs”), are capable of specifically binding to selected targets and modulating the target's activity, e.g., through binding aptamers may block their target's ability to function. Created by an in vitro selection process from pools of random sequence oligonucleotides, aptamers have been generated for over 100 proteins including growth factors, transcription factors, enzymes, immunoglobulins, and receptors. A typical aptamer is 10-15 kDa in size (30-45 nucleotides), binds its target with sub-nanomolar affinity, and discriminates against closely related targets (e.g., aptamers will typically not bind other proteins from the same gene family). A series of structural studies have shown that aptamers are capable of using the same types of binding interactions (e.g., hydrogen bonding, electrostatic complementarity, hydrophobic contacts, steric exclusion) that drive affinity and specificity in antibody-antigen complexes.

Aptamers have a number of desirable characteristics for use as therapeutics and diagnostics including high specificity and affinity, biological efficacy, and excellent pharmacokinetic properties. In addition, they offer specific competitive advantages over antibodies and other protein biologics, for example:

Speed and control. Aptamers are produced by an entirely in vitro process, allowing for the rapid generation of initial leads, including therapeutic leads. In vitro selection allows the specificity and affinity of the aptamer to be tightly controlled and allows the generation of leads, including leads against both toxic and non-immunogenic targets.

Toxicity and Immunogenicity. Aptamers as a class have demonstrated little or no toxicity or immunogenicity. In chronic dosing of rats or woodchucks with high levels of aptamer (10 mg/kg daily for 90 days), no toxicity is observed by any clinical, cellular, or biochemical measure. Whereas the efficacy of many monoclonal antibodies can be severely limited by immune response to antibodies themselves, it is extremely difficult to elicit antibodies to aptamers most likely because aptamers cannot be presented by T-cells via the MHC and the immune response is generally trained not to recognize nucleic acid fragments.

Administration. Whereas most currently approved antibody therapeutics are administered by intravenous infusion (typically over 2-4 hours), aptamers can be administered by subcutaneous injection (aptamer bioavailability via subcutaneous administration is >80% in monkey studies (Tucker et al., J. Chromatography B. 732: 203-212, 1999)). This difference is primarily due to the comparatively low solubility and thus large volumes necessary for most therapeutic mAbs. With good solubility (>150 mg/mL) and comparatively low molecular weight (aptamer: 10-50 kDa; antibody: 150 kDa), a weekly dose of aptamer may be delivered by injection in a volume of less than 0.5 mL. In addition, the small size of aptamers allows them to penetrate into areas of conformational constrictions that do not allow for antibodies or antibody fragments to penetrate, presenting yet another advantage of aptamer-based therapeutics or prophylaxis.

Scalability and cost. Aptamers are chemically synthesized and are readily scaled as needed to meet production demand for diagnostic or therapeutic applications. Whereas difficulties in scaling production are currently limiting the availability of some biologics and the capital cost of a large-scale protein production plant is enormous, a single large-scale oligonucleotide synthesizer can produce upwards of 100 kg/year and requires a relatively modest initial investment. The current cost of goods for aptamer synthesis at the kilogram scale is estimated at $100/g, comparable to that for highly optimized antibodies.

Stability. Aptamers are chemically robust. They are intrinsically adapted to regain activity following exposure to factors such as heat and denaturants and can be stored for extended periods (>1 yr) at room temperature as lyophilized powders.

INCORPORATION BY REFERENCE

All publications, patents and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated by reference.

SUMMARY OF THE INVENTION

Compositions and methods of the invention provide aptamers that are useful in assays to detect biomarkers. One aspect of the invention provides methods of selecting aptamers of interest that specifically bind to one or more antigens in a biological sample of interest. In some embodiments of the invention, an aptamer or a plurality of aptamer molecules are identified, which are configured to bind to or associate with a plurality of target molecules present in one or more biological samples. The biological sample may comprise a population or subpopulation of microvesicles as further described herein.

In an aspect, the invention provides a method of identifying one or more aptamer comprising: (a) providing a pool of candidate aptamers; (b) contacting a first one or more biological sample with the pool provided in step (a), wherein the first one or more biological sample comprises a heterogeneous microvesicle population or a homogeneous microvesicle population; (c) identifying a first subpool of candidate aptamers that bound one or more microvesicle in the first one or more biological sample in step (b); (d) contacting a second one or more biological sample with the pool provided in step (a), wherein the second one or more biological sample comprises a heterogeneous microvesicle population or a homogeneous microvesicle population; (e) identifying a second subpool of candidate aptamers that bound one or more microvesicle in the second one or more biological sample in step (d); and (f) comparing the members of the first and second subpools of candidate aptamers to identify one or more member of a pool that is overrepresented in one of the subpools versus the other subpool, thereby identifying the one or more aptamer. The one or more aptamer identified in step (f) may be partially or wholly found in the overrepresented subpool and absent in the other subpool.

The pool of candidate aptamers contacted with the biological samples can be different aliquots of the same pool. In some embodiments, members of the plurality of first biological samples are separately contacted with aliquots of the pool in step (b). In addition, members of the plurality of first biological samples can be separately contacted with aliquots of the pool in step (d). The plurality can comprise any number of desired samples, e.g., at least two samples. In embodiments, the plurality of samples comprises at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or at least 100 samples.

The selection of aptamers that bind the microvesicles can be repeated in an iterative manner. In some embodiments, the method of the invention further comprising repeating steps (b)-(c) at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 times prior to step (f), wherein the first subpool of candidate aptamers from step (c) is used as the starting pool of candidate aptamers when repeating step (b). In addition, steps (d)-(e) can be repeated at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 times prior to step (f), wherein the second subpool of candidate aptamers from step (e) is used as the starting pool of candidate aptamers when repeating step (d). In some embodiments, the method comprises repeating steps (a)-(f) at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 times, wherein the identified one or more aptamer from step (f) is used as the starting pool of candidate aptamers when repeating step (a).

It is understood that the method of the invention can identify one or more aptamer that preferentially distinguishes the microvesicles in the first and second samples. In some embodiments, the first one or more biological sample comprises a diseased sample. Each of the first one or more biological samples may comprise a sample representative of the same disease. In such embodiments, the second one or more biological sample may comprise a non-diseased sample. Such embodiments can allow the identification of aptamers that distinguish microvesicles in diseased versus non diseased samples. In other embodiments, the first one or more biological sample comprises the same disease as the second one or more biological sample, and wherein the disease in the first and second samples differs in one of more of clinical stage, pathologic stage, aggressiveness, growth rate, receptor status, prior treatment, response to a same to treatment, and response to different treatments. Such embodiments can allow the identification of aptamers that distinguish microvesicles between various states or progression of a disease.

In preferred embodiments, the disease comprises a cancer. The cancer can be any appropriate cancer. For example, the cancer may be an acute lymphoblastic leukemia; acute myeloid leukemia; adrenocortical carcinoma; AIDS-related cancers; AIDS-related lymphoma; anal cancer; appendix cancer; astrocytomas; atypical teratoid/rhabdoid tumor; basal cell carcinoma; bladder cancer; brain stem glioma; brain tumor (including brain stem glioma, central nervous system atypical teratoid/rhabdoid tumor, central nervous system embryonal tumors, astrocytomas, craniopharyngioma, ependymoblastoma, ependymoma, medulloblastoma, medulloepithelioma, pineal parenchymal tumors of intermediate differentiation, supratentorial primitive neuroectodermal tumors and pineoblastoma); breast cancer; bronchial tumors; Burkitt lymphoma; cancer of unknown primary site; carcinoid tumor; carcinoma of unknown primary site; central nervous system atypical teratoid/rhabdoid tumor; central nervous system embryonal tumors; cervical cancer; childhood cancers; chordoma; chronic lymphocytic leukemia; chronic myelogenous leukemia; chronic myeloproliferative disorders; colon cancer; colorectal cancer; craniopharyngioma; cutaneous T-cell lymphoma; endocrine pancreas islet cell tumors; endometrial cancer; ependymoblastoma; ependymoma; esophageal cancer; esthesioneuroblastoma; Ewing sarcoma; extracranial germ cell tumor; extragonadal germ cell tumor; extrahepatic bile duct cancer; gallbladder cancer; gastric (stomach) cancer; gastrointestinal carcinoid tumor; gastrointestinal stromal cell tumor; gastrointestinal stromal tumor (GIST); gestational trophoblastic tumor; glioma; hairy cell leukemia; head and neck cancer; heart cancer; Hodgkin lymphoma; hypopharyngeal cancer; intraocular melanoma; islet cell tumors; Kaposi sarcoma; kidney cancer; Langerhans cell histiocytosis; laryngeal cancer; lip cancer; liver cancer; lung cancer; malignant fibrous histiocytoma bone cancer; medulloblastoma; medulloepithelioma; melanoma; Merkel cell carcinoma; Merkel cell skin carcinoma; mesothelioma; metastatic squamous neck cancer with occult primary; mouth cancer; multiple endocrine neoplasia syndromes; multiple myeloma; multiple myeloma/plasma cell neoplasm; mycosis fungoides; myelodysplastic syndromes; myeloproliferative neoplasms; nasal cavity cancer; nasopharyngeal cancer; neuroblastoma; Non-Hodgkin lymphoma; nonmelanoma skin cancer; non-small cell lung cancer; oral cancer; oral cavity cancer; oropharyngeal cancer; osteosarcoma; other brain and spinal cord tumors; ovarian cancer; ovarian epithelial cancer; ovarian germ cell tumor; ovarian low malignant potential tumor; pancreatic cancer; papillomatosis; paranasal sinus cancer; parathyroid cancer; pelvic cancer; penile cancer; pharyngeal cancer; pineal parenchymal tumors of intermediate differentiation; pineoblastoma; pituitary tumor; plasma cell neoplasm/multiple myeloma; pleuropulmonary blastoma; primary central nervous system (CNS) lymphoma; primary hepatocellular liver cancer; prostate cancer; rectal cancer; renal cancer; renal cell (kidney) cancer; renal cell cancer; respiratory tract cancer; retinoblastoma; rhabdomyosarcoma; salivary gland cancer; Sézary syndrome; small cell lung cancer; small intestine cancer; soft tissue sarcoma; squamous cell carcinoma; squamous neck cancer; stomach (gastric) cancer; supratentorial primitive neuroectodermal tumors; T-cell lymphoma; testicular cancer; throat cancer; thymic carcinoma; thymoma; thyroid cancer; transitional cell cancer; transitional cell cancer of the renal pelvis and ureter; trophoblastic tumor; ureter cancer; urethral cancer; uterine cancer; uterine sarcoma; vaginal cancer; vulvar cancer; Waldenström macroglobulinemia; or Wilm's tumor. The disease can be, e.g., a prostate cancer, a lung cancer, a breast cancer, a brain cancer, an ovarian cancer, a colorectal cancer, or a melanoma.

In embodiments of the method of the invention, the first one or more biological sample comprises a bodily fluid. The second one or more biological sample may also comprise a bodily fluid. Any appropriate bodily fluid can be used, e.g., any bodily fluid containing microvesicles. For example, the bodily fluid can comprise peripheral blood, sera, plasma, ascites, urine, cerebrospinal fluid (CSF), sputum, saliva, bone marrow, synovial fluid, aqueous humor, amniotic fluid, cerumen, breast milk, broncheoalveolar lavage fluid, semen, prostatic fluid, cowper's fluid or pre-ejaculatory fluid, female ejaculate, sweat, fecal matter, hair, tears, cyst fluid, pleural and peritoneal fluid, pericardial fluid, lymph, chyme, chyle, bile, interstitial fluid, menses, pus, sebum, vomit, vaginal secretions, mucosal secretion, stool water, pancreatic juice, lavage fluids from sinus cavities, bronchopulmonary aspirates, blastocyl cavity fluid, umbilical cord blood, or a derivative of any thereof. In some embodiments, the bodily fluid comprises peripheral blood, plasma, serum or a derivative of any thereof. Thus, the microvesicles assessed are those found in blood. The biological sample can be a tissue sample or cell culture sample. As a non-limiting example, microvesicles shed from a particular cancer cell line or cancer tissue can be compared to those shed from a normal cell line or normal tissue. One of skill will appreciate that any appropriate sample types of a desired phenotype can be used to identify aptamers according to the subject method.

The identifying in step (c) and/or step (e) can include sequencing the candidate aptamers that bound the one or more microvesicle. As described more herein, any appropriate sequencing technology can be used, e.g., dye termination (Sanger) sequencing or high throughput sequencing methods (e.g., Next Generation sequencing technologies). High throughput/Next generation methods comprise techiques to rapidly sequence a large number of nucleic acids, including without limitation next generation techniques such as Massively parallel signature sequencing (MPSS; Polony sequencing; 454 pyrosequencing; Illumina (Solexa) sequencing; SOLiD sequencing; Ion Torrent semiconductor sequencing; DNA nanoball sequencing; Heliscope single molecule sequencing; Single molecule real time (SMRT) sequencing, or other methods such as Nanopore DNA sequencing; Tunnelling currents DNA sequencing; Sequencing by hybridization; Sequencing with mass spectrometry; Microfluidic Sanger sequencing; Microscopy-based techniques; RNAP sequencing; In vitro virus high-throughput sequencing. Comparing the members of the first and second subpools in step (f) may comprise comparing the sequences of the aptamers identified in step (c) and/or step (e).

The candidate aptamers identified according to the method of the invention can bind one or more microvesicle surface antigen of the one or more microvesicle. The aptamers may bind to any appropriate surface antigen, including without limitation one or more microvesicle surface antigen selected from Table 2 and/or Table 3. One of skill will appreciate that the method can identify aptamers that differentiate between the input samples without knowing the precise microvesicle antigen of the aptamer. In some embodiments, the method of the invention further comprises identifying the antigen of the one or more microvesicle recognized by the identified one or more aptamer. Techniques to identify the antigen of an aptamer are disclosed further herein or techniques known in the art can be used.

The method of the invention may further comprise filtering the identified one or more aptamer. For example, such filtering may be performed to refine the identified one or more aptamer to have certain desired characteristics. Filtering the identified one or more aptamer can comprise calculating a stability of the one or more aptamer. In some embodiments, filtering includes identifying a secondary structure of the one or more aptamer. The filtering can also include separately contacting each of the one or more aptamer with a biological sample. Any combination of such filtering methods can be used according to the subject invention.

In a related aspect, the invention provides a method of detecting a presence or level of one or more microvesicle in a biological sample, comprising contacting the biological sample with one or more aptamer identified according the method described above. The detection method can further comprise comparing the detected presence or level of the one or more microvesicle with a reference presence or level. The reference can be a normal or control level. In some embodiments, such comparison provides a diagnosis, prognosis or theranosis of a disease, e.g., of a cancer as described above.

In still another related aspect, the invention contemplates use of one or more reagent for carrying out the methods of the invention above. The invention also contemplates use of one or more reagent for the manufacture of a kit, a reagent and/or a composition for carrying out the methods of the invention above. Similarly, the invention contemplates a kit comprising one or more reagent for carrying out the methods of the invention above. The one or more reagent can comprise the pool of candidate aptamers provided in step (a), e.g., as relates to the method of identifying the one or more aptamer, and/or the identified one or more aptamer, e.g., as relates to the method of detecting a microvesicle.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1F illustrate methods of assessing biomarkers such as microvesicle surface antigens. FIG. 1A is a schematic of a planar substrate coated with a capture agent, such as an aptamer or antibody, which captures vesicles expressing the target antigen of the capture agent. The capture agent may bind a protein expressed on the surface of vesicles shed from diseased cells (“disease vesicle”). The detection agent, which may also be an aptamer or antibody, carries a detectable label, here a fluorescent signal. The detection agent binds to the captured vesicle and provides a detectable signal via its fluorescent label. The detection agent can detect an antigen that is generally associated with vesicles, or is associated with a cell-of-origin or a disease, e.g., a cancer. FIG. 1B is a schematic of a particle bead conjugated with a capture agent, which captures vesicles expressing the target antigen of the capture agent. The capture agent may bind a protein expressed on the surface of vesicles shed from diseased cells (“disease vesicle”). The detection agent, which may also be an aptamer or antibody, carries a detectable label, here a fluorescent signal. The detection agent binds to the captured vesicle and provides a detectable signal via its fluorescent label. The detection agent can detect an antigen that is generally associated with vesicles, or is associated with a cell-of-origin or a disease, e.g., a cancer. FIG. 1C is an example of a screening scheme that can be performed by using different combinations of capture and detection agents to the indicated biomarkers. The biomarker combinations can be detected using assays as shown in FIGS. 1A-1B. FIGS. 1D-1E present illustrative schemes for capturing and detecting vesicles to characterize a phenotype. FIG. 1F presents illustrative schemes for assessing vesicle payload to characterize a phenotype.

FIGS. 2A-B illustrates a method of selecting a binding agent, e.g., an aptamer, from a pool of candidate binding agents. FIG. 2C illustrates how binding agents selected from the pool can be used to distinguish one or more biological samples.

FIGS. 3A-3D illustrate the use of an anti-EpCAM aptamer (Aptamer 4; SEQ ID NO. 10) to detect a microvesicle population. Vesicles in patient plasma samples were captured using bead-conjugated antibodies to the indicated microvesicle surface antigens: FIG. 3A) EGFR; FIG. 3B) PBP; FIG. 3C) EpCAM; and FIG. 3D) KLK2. Fluorescently labeled Aptamer 4 was used as a detector in the microbead assay. The figures show average median fluorescence values (MFI values) for three cancer (C1-C3) and three normal samples (N1-N3) in each plot. In each plot, the samples from left to right are ordered as: C1, C2, C3, N1, N2, N3.

FIGS. 4A-B illustrate binding of selected aptamers against microbeads conjugated to various input samples. The aptamers were selected from an aptamer library as binding to microbeads conjugated to breast cancer-derived microvesicles from plasma and not to normal microvesicles. Further experimental details are in Example 9. Each plot shows results obtained with the aptamer indicated above the plot. The Y-axis indicates level of binding. The input sample is indicated on the X axis from left to right as follows: 1) Cancer Exosome: aptamer binding to microbeads conjugated to microvesicles isolated from plasma samples from breast cancer patients; 2) Cancer Non-exosome: aptamer binding to microbeads conjugated to plasma samples from breast cancer patients after removal of microvesicles by ultracentrifugation; 3) Non-Cancer Exosome: aptamer binding to microbeads conjugated to microvesicles isolated from plasma samples from normal (i.e., non-breast cancer) patients; 4) Non-Cancer Non-Exosome: aptamer binding to microbeads conjugated to plasma samples from breast cancer patients after removal of microvesicles by ultracentrifugation.

DETAILED DESCRIPTION OF THE INVENTION

The details of one or more embodiments of the invention are set forth in the accompanying description below. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, the preferred methods and materials are now described. Other features, objects, and advantages of the invention will be apparent from the description. In the specification, the singular forms also include the plural unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. In the case of conflict, the present Specification will control.

Disclosed herein are methods of selecting aptamers, and compositions and methods using selected aptamers to detect aptamer targets. In general, aptamers disclosed are nucleic acid molecules and variations thereof. The methods disclosed also comprise detection assays that make use of the aptamers herein, including diagnostic processes and techniques using one or more aptamer of the invention.

In one aspect of the invention, methods are directed to assessing various biological sample inputs to identify a plurality of binding agents that selectively bind to or associate with biomarkers present in a selected biological sample. As further described herein below, multiple different pools or sets of binding agents, such as aptamers, can be selected and identified (e.g., through sequencing) that are capable of selectively binding to one first input biological sample and not another second (or third, fourth, fifth, sixth, or more) additional biological sample. As such various “sets” of aptamers can be selected that function to distinguish one biological sample from another biological sample. The aptamer sets can themselves function to distinguish one biological sample from another (e.g., a set specific for a specific condition can identify a sample as coming from a subject with such condition versus a subject not having said condition).

Furthermore, the aptamer sets can be further utilized to identify each individual target molecule, at the level of a single aptamer-to-cognate target molecule, using cross-linking or other conventional technologies (as further discussed below).

Aptamers

SELEX. A suitable method for generating an aptamer is with the process entitled “Systematic Evolution of Ligands by Exponential Enrichment” (“SELEX”) generally described in, e.g., U.S. patent application Ser. No. 07/536,428, filed Jun. 11, 1990, now abandoned, U.S. Pat. No. 5,475,096 entitled “Nucleic Acid Ligands”, and U.S. Pat. No. 5,270,163 (see also WO 91/19813) entitled “Nucleic Acid Ligands”. Each SELEX-identified nucleic acid ligand, i.e., each aptamer, is a specific ligand of a given target compound or molecule. The SELEX process is based on the unique insight that nucleic acids have sufficient capacity for forming a variety of two- and three-dimensional structures and sufficient chemical versatility available within their monomers to act as ligands (i.e., form specific binding pairs) with virtually any chemical compound, whether monomeric or polymeric. Molecules of any size or composition can serve as targets.

SELEX relies as a starting point upon a large library or pool of single stranded oligonucleotides comprising randomized sequences. The oligonucleotides can be modified or unmodified DNA, RNA, or DNA/RNA hybrids. In some examples, the pool comprises 100% random or partially random oligonucleotides. In other examples, the pool comprises random or partially random oligonucleotides containing at least one fixed and/or conserved sequence incorporated within randomized sequence. In other examples, the pool comprises random or partially random oligonucleotides containing at least one fixed and/or conserved sequence at its 5′ and/or 3′ end which may comprise a sequence shared by all the molecules of the oligonucleotide pool. Fixed sequences are sequences such as hybridization sites for PCR primers, promoter sequences for RNA polymerases (e.g., T3, T4, T7, and SP6), restriction sites, or homopolymeric sequences, such as poly A or poly T tracts, catalytic cores, sites for selective binding to affinity columns, and other sequences to facilitate cloning and/or sequencing of an oligonucleotide of interest. Conserved sequences are sequences, other than the previously described fixed sequences, shared by a number of aptamers that bind to the same target.

The oligonucleotides of the pool preferably include a randomized sequence portion as well as fixed sequences necessary for efficient amplification. Typically the oligonucleotides of the starting pool contain fixed 5′ and 3′ terminal sequences which flank an internal region of 30-50 random nucleotides. The randomized nucleotides can be produced in a number of ways including chemical synthesis and size selection from randomly cleaved cellular nucleic acids. Sequence variation in test nucleic acids can also be introduced or increased by mutagenesis before or during the selection/amplification iterations.

The random sequence portion of the oligonucleotide can be of any length and can comprise ribonucleotides and/or deoxyribonucleotides and can include modified or non-natural nucleotides or nucleotide analogs. See, e.g. U.S. Pat. No. 5,958,691; U.S. Pat. No. 5,660,985; U.S. Pat. No. 5,958,691; U.S. Pat. No. 5,698,687; U.S. Pat. No. 5,817,635; U.S. Pat. No. 5,672,695, and PCT Publication WO 92/07065. Random oligonucleotides can be synthesized from phosphodiester-linked nucleotides using solid phase oligonucleotide synthesis techniques well known in the art. See, e.g., Froehler et al., Nucl. Acid Res. 14:5399-5467 (1986) and Froehler et al., Tet. Lett. 27:5575-5578 (1986). Random oligonucleotides can also be synthesized using solution phase methods such as triester synthesis methods. See, e.g., Sood et al., Nucl. Acid Res. 4:2557 (1977) and Hirose et al., Tet. Lett., 28:2449 (1978). Typical syntheses carried out on automated DNA synthesis equipment yield 10¹⁴-10¹⁶ individual molecules, a number sufficient for most SELEX experiments. Sufficiently large regions of random sequence in the sequence design increases the likelihood that each synthesized molecule is likely to represent a unique sequence.

The starting library of oligonucleotides may be generated by automated chemical synthesis on a DNA synthesizer. To synthesize randomized sequences, mixtures of all four nucleotides are added at each nucleotide addition step during the synthesis process, allowing for random incorporation of nucleotides. As stated above, in one embodiment, random oligonucleotides comprise entirely random sequences; however, in other embodiments, random oligonucleotides can comprise stretches of nonrandom or partially random sequences. Partially random sequences can be created by adding the four nucleotides in different molar ratios at each addition step.

The starting library of oligonucleotides may be for example, RNA, DNA, or RNA/DNA hybrid. In those instances where an RNA library is to be used as the starting library it is typically generated by transcribing a DNA library in vitro using T7 RNA polymerase or modified T7 RNA polymerases and purified. The library is then mixed with the target under conditions favorable for binding and subjected to step-wise iterations of binding, partitioning and amplification, using the same general selection scheme, to achieve virtually any desired criterion of binding affinity and selectivity. More specifically, starting with a mixture containing the starting pool of nucleic acids, the SELEX method includes steps of: (a) contacting the mixture with the target under conditions favorable for binding; (b) partitioning unbound nucleic acids from those nucleic acids which have bound specifically to target molecules; (c) dissociating the nucleic acid-target complexes; (d) amplifying the nucleic acids dissociated from the nucleic acid-target complexes to yield a ligand-enriched mixture of nucleic acids; and (e) reiterating the steps of binding, partitioning, dissociating and amplifying through as many cycles as desired to yield highly specific, high affinity nucleic acid ligands to the target molecule. In those instances where RNA aptamers are being selected, the SELEX method further comprises the steps of: (i) reverse transcribing the nucleic acids dissociated from the nucleic acid-target complexes before amplification in step (d); and (ii) transcribing the amplified nucleic acids from step (d) before restarting the process.

Within a nucleic acid mixture containing a large number of possible sequences and structures, there is a wide range of binding affinities for a given target. A nucleic acid mixture comprising, for example, a 20 nucleotide randomized segment can have 4²⁰ candidate possibilities. Those which have the higher affinity constants for the target are most likely to bind to the target. After partitioning, dissociation and amplification, a second nucleic acid mixture is generated, enriched for the higher binding affinity candidates. Additional rounds of selection progressively favor improved ligands until the resulting nucleic acid mixture is predominantly composed of only one or a few sequences. These can then be cloned, sequenced and individually tested for binding affinity as pure ligands or aptamers.

Cycles of selection and amplification are repeated until a desired goal is achieved. In the most general case, selection/amplification is continued until no significant improvement in binding strength is achieved on repetition of the cycle. The method is typically used to sample approximately 10¹⁴ different nucleic acid species but may be used to sample as many as about 10¹⁸ different nucleic acid species. Generally, nucleic acid aptamer molecules are selected in a 5 to 20 cycle procedure. In one embodiment, heterogeneity is introduced only in the initial selection stages and does not occur throughout the replicating process.

In one embodiment of SELEX, the selection process is so efficient at isolating those nucleic acid ligands that bind most strongly to the selected target, that only one cycle of selection and amplification is required. Such an efficient selection may occur, for example, in a chromatographic-type process wherein the ability of nucleic acids to associate with targets bound on a column operates in such a manner that the column is sufficiently able to allow separation and isolation of the highest affinity nucleic acid ligands.

In many cases, it is not necessarily desirable to perform the iterative steps of SELEX until a single nucleic acid ligand is identified. The target-specific nucleic acid ligand solution may include a family of nucleic acid structures or motifs that have a number of conserved sequences and a number of sequences which can be substituted or added without significantly affecting the affinity of the nucleic acid ligands to the target. By terminating the SELEX process prior to completion, it is possible to determine the sequence of a number of members of the nucleic acid ligand solution family.

A variety of nucleic acid primary, secondary and tertiary structures are known to exist. The structures or motifs that have been shown most commonly to be involved in non-Watson-Crick type interactions are referred to as hairpin loops, symmetric and asymmetric bulges, pseudoknots and myriad combinations of the same. Almost all known cases of such motifs suggest that they can be formed in a nucleic acid sequence of no more than 30 nucleotides. For this reason, it is often preferred that SELEX procedures with contiguous randomized segments be initiated with nucleic acid sequences containing a randomized segment of between about 20 to about 50 nucleotides and in some embodiments, about 30 to about 40 nucleotides. In one example, the 5′-fixed:random:3′-fixed sequence comprises a random sequence of about 30 to about 50 nucleotides.

The core SELEX method has been modified to achieve a number of specific objectives. For example, U.S. Pat. No. 5,707,796 describes the use of SELEX in conjunction with gel electrophoresis to select nucleic acid molecules with specific structural characteristics, such as bent DNA. U.S. Pat. No. 5,763,177 describes SELEX based methods for selecting nucleic acid ligands containing photoreactive groups capable of binding and/or photocrosslinking to and/or photoinactivating a target molecule. U.S. Pat. No. 5,567,588 and U.S. Pat. No. 5,861,254 describe SELEX based methods which achieve highly efficient partitioning between oligonucleotides having high and low affinity for a target molecule. U.S. Pat. No. 5,496,938 describes methods for obtaining improved nucleic acid ligands after the SELEX process has been performed. U.S. Pat. No. 5,705,337 describes methods for covalently linking a ligand to its target.

SELEX can also be used to obtain nucleic acid ligands that bind to more than one site on the target molecule, and to obtain nucleic acid ligands that include non-nucleic acid species that bind to specific sites on the target. SELEX provides means for isolating and identifying nucleic acid ligands which bind to any envisionable target, including large and small biomolecules such as nucleic acid-binding proteins and proteins not known to bind nucleic acids as part of their biological function as well as cofactors and other small molecules. For example, U.S. Pat. No. 5,580,737 discloses nucleic acid sequences identified through SELEX which are capable of binding with high affinity to caffeine and the closely related analog, theophylline.

Counter-SELEX is a method for improving the specificity of nucleic acid ligands to a target molecule by eliminating nucleic acid ligand sequences with cross-reactivity to one or more non-target molecules. Counter-SELEX is comprised of the steps of: (a) preparing a candidate mixture of nucleic acids; (b) contacting the candidate mixture with the target, wherein nucleic acids having an increased affinity to the target relative to the candidate mixture may be partitioned from the remainder of the candidate mixture; (c) partitioning the increased affinity nucleic acids from the remainder of the candidate mixture; (d) dissociating the increased affinity nucleic acids from the target; e) contacting the increased affinity nucleic acids with one or more non-target molecules such that nucleic acid ligands with specific affinity for the non-target molecule(s) are removed; and (f) amplifying the nucleic acids with specific affinity only to the target molecule to yield a mixture of nucleic acids enriched for nucleic acid sequences with a relatively higher affinity and specificity for binding to the target molecule. As described above for SELEX, cycles of selection and amplification are repeated as necessary until a desired goal is achieved.

One potential problem encountered in the use of nucleic acids as therapeutics and vaccines is that oligonucleotides in their phosphodiester form may be quickly degraded in body fluids by intracellular and extracellular enzymes such as endonucleases and exonucleases before the desired effect is manifest. The SELEX method thus encompasses the identification of high-affinity nucleic acid ligands containing modified nucleotides conferring improved characteristics on the ligand, such as improved in vivo stability or improved delivery characteristics. Examples of such modifications include chemical substitutions at the ribose and/or phosphate and/or base positions. SELEX identified nucleic acid ligands containing modified nucleotides are described, e.g., in U.S. Pat. No. 5,660,985, which describes oligonucleotides containing nucleotide derivatives chemically modified at the 2′ position of ribose, 5 position of pyrimidines, and 8 position of purines, U.S. Pat. No. 5,756,703 which describes oligonucleotides containing various 2′-modified pyrimidines, and U.S. Pat. No. 5,580,737 which describes highly specific nucleic acid ligands containing one or more nucleotides modified with 2′-amino(2′-NH₂), 2′-fluoro (2′-F), and/or 2′-O-methyl(2′-OMe) substituents.

Modifications of the nucleic acid ligands contemplated in this invention include, but are not limited to, those which provide other chemical groups that incorporate additional charge, polarizability, hydrophobicity, hydrogen bonding, electrostatic interaction, and fluxionality to the nucleic acid ligand bases or to the nucleic acid ligand as a whole. Modifications to generate oligonucleotide populations which are resistant to nucleases can also include one or more substitute internucleotide linkages, altered sugars, altered bases, or combinations thereof. Such modifications include, but are not limited to, 2′-position sugar modifications, 5-position pyrimidine modifications, 8-position purine modifications, modifications at exocyclic amines, substitution of 4-thiouridine, substitution of 5-bromo or 5-iodo-uracil; backbone modifications, phosphorothioate or allyl phosphate modifications, methylations, and unusual base-pairing combinations such as the isobases isocytidine and isoguanosine. Modifications can also include 3′ and 5′ modifications such as capping.

In one embodiment, oligonucleotides are provided in which the P(O)O group is replaced by P(O)S (“thioate”), P(S)S (“dithioate”), P(O)NR₂ (“amidate”), P(O)R, P(O)OR′, CO or CH₂ (“formacetal”) or 3′-amine (—NH—CH₂—CH₂—), wherein each R or R′ is independently H or substituted or unsubstituted alkyl. Linkage groups can be attached to adjacent nucleotides through an —O—, —N—, or —S— linkage. Not all linkages in the oligonucleotide are required to be identical. As used herein, the term phosphorothioate encompasses one or more non-bridging oxygen atoms in a phosphodiester bond replaced by one or more sulfur atoms.

In further embodiments, the oligonucleotides comprise modified sugar groups, for example, one or more of the hydroxyl groups is replaced with halogen, aliphatic groups, or functionalized as ethers or amines. In one embodiment, the 2′-position of the furanose residue is substituted by any of an O-methyl, O-alkyl, O-allyl, S-alkyl, S-allyl, or halo group. Methods of synthesis of 2′-modified sugars are described, e.g., in Sproat, et al., Nucl. Acid Res. 19:733-738 (1991); Cotten, et al., Nucl. Acid Res. 19:2629-2635 (1991); and Hobbs, et al., Biochemistry 12:5138-5145 (1973). Other modifications are known to one of ordinary skill in the art. Such modifications may be pre-SELEX process modifications or post-SELEX process modifications (modification of previously identified unmodified ligands) or may be made by incorporation into the SELEX process.

Pre-SELEX process modifications or those made by incorporation into the SELEX process yield nucleic acid ligands with both specificity for their SELEX target and improved stability, e.g., in vivo stability. Post-SELEX process modifications made to nucleic acid ligands may result in improved stability, e.g., in vivo stability without adversely affecting the binding capacity of the nucleic acid ligand.

The SELEX method encompasses combining selected oligonucleotides with other selected oligonucleotides and non-oligonucleotide functional units as described in U.S. Pat. No. 5,637,459 and U.S. Pat. No. 5,683,867. The SELEX method further encompasses combining selected nucleic acid ligands with lipophilic or non-immunogenic high molecular weight compounds in a diagnostic or therapeutic complex, as described, e.g., in U.S. Pat. No. 6,011,020, U.S. Pat. No. 6,051,698, and PCT Publication No. WO 98/18480. These patents and applications teach the combination of a broad array of shapes and other properties, with the efficient amplification and replication properties of oligonucleotides, and with the desirable properties of other molecules.

The identification of nucleic acid ligands to small, flexible peptides via the SELEX method has also been explored. Small peptides have flexible structures and usually exist in solution in an equilibrium of multiple conformers, and thus it was initially thought that binding affinities may be limited by the conformational entropy lost upon binding a flexible peptide. However, the feasibility of identifying nucleic acid ligands to small peptides in solution was demonstrated in U.S. Pat. No. 5,648,214. In this patent, high affinity RNA nucleic acid ligands to substance P, an 11 amino acid peptide, were identified.

The aptamers with specificity and binding affinity to the target(s) of the present invention can be selected by the SELEX N process as described herein. As part of the SELEX process, the sequences selected to bind to the target are then optionally minimized to determine the minimal sequence having the desired binding affinity. The selected sequences and/or the minimized sequences are optionally optimized by performing random or directed mutagenesis of the sequence to increase binding affinity or alternatively to determine which positions in the sequence are essential for binding activity. Additionally, selections can be performed with sequences incorporating modified nucleotides to stabilize the aptamer molecules against degradation in vivo.

2′ Modified SELEX. In order for an aptamer to be suitable for use as a therapeutic, it is preferably inexpensive to synthesize, safe and stable in vivo. Wild-type RNA and DNA aptamers are typically not stable is vivo because of their susceptibility to degradation by nucleases. Resistance to nuclease degradation can be greatly increased by the incorporation of modifying groups at the 2′-position.

Fluoro and amino groups have been successfully incorporated into oligonucleotide pools from which aptamers have been subsequently selected. However, these modifications greatly increase the cost of synthesis of the resultant aptamer, and may introduce safety concerns in some cases because of the possibility that the modified nucleotides could be recycled into host DNA by degradation of the modified oligonucleotides and subsequent use of the nucleotides as substrates for DNA synthesis.

Aptamers that contain 2′-O-methyl (“2′-OMe”) nucleotides, as provided herein, may overcome many of these drawbacks. Oligonucleotides containing 2′-OMe nucleotides are nuclease-resistant and inexpensive to synthesize. Although 2′-OMe nucleotides are ubiquitous in biological systems, natural polymerases do not accept 2′-OMe NTPs as substrates under physiological conditions, thus there are no safety concerns over the recycling of 2′-OMe nucleotides into host DNA. The SELEX method used to generate 2″-modified aptamers is described, e.g., in U.S. Provisional Patent Application Ser. No. 60/430,761, filed Dec. 3, 2002, U.S. Provisional Patent Application Ser. No. 60/487,474, filed Jul. 15, 2003, U.S. Provisional Patent Application Ser. No. 60/517,039, filed Nov. 4, 2003, U.S. patent application Ser. No. 10/729,581, filed Dec. 3, 2003, and U.S. patent application Ser. No. 10/873,856, filed Jun. 21, 2004, entitled “Method for in vitro Selection of 2′-O-methyl substituted Nucleic Acids”, each of which is herein incorporated by reference in its entirety.

Additional examples of aptamers modifications that are used in various embodiments of the invention are found in US Patent Publication Nos. 20110275794, 20120101002, 20120077695, each of which is herein incorporated by reference in its entirety.

METHODS

Biomarker Detection and Diagnostics

The aptamers of the invention can be used in various methods to assess presence or level of biomarkers in a biological sample, e.g., biological entities of interest such as proteins, nucleic acids, or microvesicles. The aptamer functions as a binding agent to assess presence or level of the cognate target molecule. Therefore, in various embodiments of the invention directed to diagnostics, prognostics or theranostics, one or more aptamers of the invention are configured in a ligand-target based assay, where one or more aptamer of the invention is contacted with a selected biological sample, where the or more aptamer associates with or binds to its target molecules. Aptamers of the invention are used to identify candidate biosignatures based on the biological samples assessed and biomarkers detected. In further embodiments, aptamers may themselves provide a biosignature for a particular condition or disease. A biosignature refers to a biomarker profile of a biological sample comprising a presence, level or other characteristic that can be assessed (including without limitation a sequence, mutation, rearrangement, translocation, deletion, epigenetic modification, methylation, post-translational modification, allele, activity, complex partners, stability, half life, and the like) of one or more biomarker of interest. Biosignatures can be used to evaluate diagnostic and/or prognostic criteria such as presence of disease, disease staging, disease monitoring, disease stratification, or surveillance for detection, metastasis or recurrence or progression of disease. For example, methods of the invention using aptamers against microvesicle surface antigen are useful for correlating a biosignature comprising microvesicle antigens to a selected condition or disease. A biosignature can also be used clinically in making decisions concerning treatment modalities including therapeutic intervention. A biosignature can further be used clinically to make treatment decisions, including whether to perform surgery or what treatment standards should be used along with surgery (e.g., either pre-surgery or post-surgery). As an illustrative example, a biosignature of circulating biomarkers that indicates an aggressive form of cancer may call for a more aggressive surgical procedure and/or more aggressive therapeutic regimen to treat the patient.

A biosignature can be used in any methods disclosed herein, e.g., to assess whether a subject is afflicted with disease, is at risk for developing disease or to assess the stage or progression of the disease. For example, a biosignature can be used to assess whether a subject has prostate cancer, colon cancer, or other cancer as described herein. Furthermore, a biosignature can be used to determine a stage of a disease or condition, such as colon cancer. The biosignature/biomarker profile comprising a microvesicle can include assessment of payload within the microvesicle. For example, one or more aptamer of the invention can be used to capture a microvesicle population, thereby providing readout of microvesicle antigens, and then the payload content within the captured microvesicles can be assessed, thereby providing further biomarker readout of the payload content.

A biosignature for characterizing a phenotype may comprise any number of useful criteria. As described further below, the term “phenotype” as used herein can mean any trait or characteristic that is attributed to a biosignature/biomarker profile. A phenotype can be detected or identified in part or in whole using the compositions and/or methods of the invention. In some embodiments, at least one criterion is used for each biomarker. In some embodiments, at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90 or at least 100 criteria are used. For example, for the characterizing of a cancer, a number of different criteria can be used when the subject is diagnosed with a cancer: 1) if the amount of microRNA in a sample from a subject is higher than a reference value; 2) if the amount of a microRNA within cell type specific vesicles (i.e. vesicles derived from a specific tissue or organ) is higher than a reference value; or 3) if the amount of microRNA within vesicles with one or more cancer specific biomarkers is higher than a reference value. Similar rules can apply if the amount of microRNA is less than or the same as the reference. The method can further include a quality control measure, such that the results are provided for the subject if the samples meet the quality control measure. In some embodiments, if the criteria are met but the quality control is questionable, the subject is reassessed.

Theranostics

A biosignature can be used in therapy related diagnostics to provide tests useful to diagnose a disease or choose the correct treatment regimen, such as provide a theranosis. Theranostics includes diagnostic testing that provides the ability to affect therapy or treatment of a diseased state. Theranostics testing provides a theranosis in a similar manner that diagnostics or prognostic testing provides a diagnosis or prognosis, respectively. As used herein, theranostics encompasses any desired form of therapy related testing, including predictive medicine, personalized medicine, integrated medicine, pharmacodiagnostics and Dx/Rx partnering. Therapy related tests can be used to predict and assess drug response in individual subjects, i.e., to provide personalized medicine. Predicting a drug response can be determining whether a subject is a likely responder or a likely non-responder to a candidate therapeutic agent, e.g., before the subject has been exposed or otherwise treated with the treatment. Assessing a drug response can be monitoring a response to a drug, e.g., monitoring the subject's improvement or lack thereof over a time course after initiating the treatment. Therapy related tests are useful to select a subject for treatment who is particularly likely to benefit from the treatment or to provide an early and objective indication of treatment efficacy in an individual subject. Thus, a biosignature as disclosed herein may indicate that treatment should be altered to select a more promising treatment, thereby avoiding the great expense of delaying beneficial treatment and avoiding the financial and morbidity costs of administering an ineffective drug(s).

The compositions and methods of the invention can be used to identify or detect a biosignature that associated with selected diseases and disorders, which include, but are not limited to cardiovascular disease, cancer, infectious diseases, sepsis, neurological diseases, central nervous system related diseases, endovascular related diseases, and autoimmune related diseases. Therapy related diagnostics also aid in the prediction of drug toxicity, drug resistance or drug response. Therapy related tests may be developed in any suitable diagnostic testing format, which include, but are not limited to, e g, immunohistochemical tests, clinical chemistry, immunoassay, cell-based technologies, nucleic acid tests or body imaging methods. Therapy related tests can further include but are not limited to, testing that aids in the determination of therapy, testing that monitors for therapeutic toxicity, or response to therapy testing. Thus, a biosignature can be used to predict or monitor a subject's response to a treatment. A biosignature can be determined at different time points for a subject after initiating, removing, or altering a particular treatment.

In some embodiments, the compositions and methods of the invention provide for a determination or prediction as to whether a subject is responding to a treatment is made based on a change in the amount of one or more components of a biosignature (i.e., the microRNA, vesicles and/or biomarkers of interest), an amount of one or more components of a particular biosignature, or the biosignature detected for the components. In another embodiment, a subject's condition is monitored by determining a biosignature at different time points. The progression, regression, or recurrence of a condition is determined. Response to therapy can also be measured over a time course. Thus, the invention provides a method of monitoring a status of a disease or other medical condition in a subject, comprising isolating or detecting a biosignature from a biological sample from the subject, detecting the overall amount of the components of a particular biosignature, or detecting the biosignature of one or more components (such as the presence, absence, or expression level of a biomarker). The biosignatures are used to monitor the status of the disease or condition.

One or more novel biosignatures of a vesicle can also be identified. For example, one or more vesicles can be isolated from a subject that responds to a drug treatment or treatment regimen and compared to a reference, such as another subject that does not respond to the drug treatment or treatment regimen. Differences between the biosignatures can be determined and used to identify other subjects as responders or non-responders to a particular drug or treatment regimen.

In some embodiments, a biosignature is used to determine whether a particular disease or condition is resistant to a drug, in which case a physician need not waste valuable time with such drug treatment. To obtain early validation of a drug choice or treatment regimen, a biosignature is determined for a sample obtained from a subject. The biosignature is used to assess whether the particular subject's disease has the biomarker associated with drug resistance. Such a determination enables doctors to devote critical time as well as the patient's financial resources to effective treatments.

Biosignatures can be used in the theranosis of a cancer, such as identifying whether a subject suffering from cancer is a likely responder or non-responder to a particular cancer treatment. The subject methods can be used to theranose cancers including those listed herein, e.g., in the “Phenotype” section above. These include without limitation lung cancer, non-small cell lung cancer small cell lung cancer (including small cell carcinoma (oat cell cancer), mixed small cell/large cell carcinoma, and combined small cell carcinoma), colon cancer, breast cancer, prostate cancer, liver cancer, pancreatic cancer, brain cancer, kidney cancer, ovarian cancer, stomach cancer, melanoma, bone cancer, gastric cancer, breast cancer, glioma, glioblastoma, hepatocellular carcinoma, papillary renal carcinoma, head and neck squamous cell carcinoma, leukemia, lymphoma, myeloma, or other solid tumors.

A biosignature of circulating biomarkers, including markers associated with a component present in a biological sample (e.g., cell, cell-fragment, cell-derived extracellular vesicle), in a sample from a subject suffering from a cancer can be used select a candidate treatment for the subject. The biosignature can be determined according to the methods of the invention presented herein. In some embodiments, the candidate treatment comprises a standard of care for the cancer. The treatment can be a cancer treatment such as radiation, surgery, chemotherapy or a combination thereof. The cancer treatment can be a therapeutic such as anti-cancer agents and chemotherapeutic regimens. Further drug associations and rules that are used in embodiments of the invention are found in U.S. patent application Ser. No. 12/658,770, filed Feb. 12, 2010; International PCT Patent Application PCT/US2010/000407, filed Feb. 11, 2010; International PCT Patent Application PCT/US2010/54366, filed Oct. 27, 2010; and U.S. Provisional Patent Application 61/427,788, filed Dec. 28, 2010; all of which applications are incorporated by reference herein in their entirety. See, e.g., “Table 4: Rules Summary for Treatment Selection” of PCT/US2010/54366.

Biomarker Detection

The compositions and methods of the invention can be used to assess any useful biomarkers in a biological sample for charactering a phenotype associated with the sample. Such biomarkers include all sorts of biological entities such as proteins, nucleic acids, lipids, carbohydrates, complexes of any thereof, and microvesicles. Various molecules associated with a microvesicle surface or enclosed within the microvesicle (referred to herein as “payload”) can serve as biomarkers. The microvesicles themselves can also be used as biomarkers.

The aptamers of the invention can be used to assess levels or presence of a microvesicle population. aptamers of the invention can also be used to assess levels or presence of their specific target molecule. In addition, aptamers of the invention are used to capture or isolated a component present in a biological sample that has the aptamer's target molecule present. For example, if a given microvesicle surface antigen is present on a cell, cell fragment or cell-derived extracellular vesicle. A binding agent to the biomarker, including without limitation an aptamer provided by the invention, may be used to capture or isolate the cell, cell fragment or cell-derived extracellular vesicles. See, e.g., FIGS. 1A-1B, 1D-1E. Such captured or isolated entities may be further characterized to assess additional surface antigens or internal “payload” molecules present (i.e., nucleic acid molecules, lipids, sugars, polypeptides or functional fragments thereof, or anything else present in the cellular milieu that may be used as a biomarker), where one or more biomarkers provide a biosignature to assess a desired phenotype, such as disease or condition. See, e.g., FIG. 1F. Therefore, aptamers of the invention are used not only to assess one or more microvesicle surface antigen of interest but are also used to separate a component present in a biological sample, where the components themselves can be further assessed to identify a candidate biosignature.

The methods of the invention can comprise multiplex analysis of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75 or 100 different biomarkers. For example, an assay of a heterogeneous population of vesicles can be performed with a plurality of particles that are differentially labeled. There can be at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75 or 100 differentially labeled particles. The particles may be externally labeled, such as with a tag, or they may be intrinsically labeled. Each differentially labeled particle can be coupled to a capture agent, such as a binding agent, for a vesicle, resulting in capture of a vesicle. The multiple capture agents can be selected to characterize a phenotype of interest, including capture agents against general vesicle biomarkers, cell-of-origin specific biomarkers, and disease biomarkers. One or more biomarkers of the captured vesicle can then be detected by a plurality of binding agents. The binding agent can be directly labeled to facilitate detection. Alternatively, the binding agent is labeled by a secondary agent. For example, the binding agent may be an antibody for a biomarker on the vesicle, wherein the binding agent is linked to biotin. A secondary agent comprises streptavidin linked to a reporter and can be added to detect the biomarker. In some embodiments, the captured vesicle is assayed for at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75 or 100 different biomarkers. For example, multiple detectors, i.e., detection of multiple biomarkers of a captured vesicle or population of vesicles, can increase the signal obtained, permitted increased sensitivity, specificity, or both, and the use of smaller amounts of samples. Detection can be with more than one biomarker, including without limitation more than one general vesicle marker such as in Table 2.

An immunoassay based method (e.g., sandwich assay) can be used to detect a biomarker of a vesicle. An example includes ELISA. A binding agent can be bound to a well. For example, a binding agent such as an aptamer or antibody to an antigen of a vesicle can be attached to a well. A biomarker on the captured vesicle can be detected based on the methods described herein. FIG. 1A shows an illustrative schematic for a sandwich-type of immunoassay. The capture agent can be against a vesicle antigen of interest, e.g., a general vesicle biomarker, a cell-of-origin marker, or a disease marker. In the figure, the captured vesicles are detected using fluorescently labeled binding agent (detection agent) against vesicle antigens of interest. Multiple capture binding agents can be used, e.g., in distinguishable addresses on an array or different wells of an immunoassay plate. The detection binding agents can be against the same antigen as the capture binding agent, or can be directed against other markers. The capture binding agent can be any useful binding agent, e.g., tethered aptamers, antibodies or lectins, and/or the detector antibodies can be similarly substituted, e.g., with detectable (e.g., labeled) aptamers, antibodies, lectins or other binding proteins or entities. In an embodiment, one or more capture agents to a general vesicle biomarker, a cell-of-origin marker, and/or a disease marker are used along with detection agents against general vesicle biomarker, such as tetraspanin molecules including without limitation one or more of CD9, CD63 and CD81, or other markers in Table 2 herein. Examples of microvesicle surface antigens are disclosed herein, e.g. in Tables 2 or 3, or are known in the art, and examples useful in methods and compositions of the invention are disclosed of International Patent Application Serial No. PCT/US2011/031479, entitled “Circulating Biomarkers for Disease” and filed Apr. 6, 2011.

FIG. 1D presents an illustrative schematic for analyzing vesicles according to the methods of the invention. Capture agents are used to capture vesicles, detectors are used to detect the captured vesicles, and the level or presence of the captured and detected microvesicles is used to characterize a phenotype. Capture agents, detectors and characterizing phenotypes can be any of those described herein. For example, capture agents include antibodies or aptamers tethered to a substrate that recognize a vesicle antigen of interest, detectors include labeled antibodies or aptamers to a vesicle antigen of interest, and characterizing a phenotype includes a diagnosis, prognosis, or theranosis of a disease. In the scheme shown in FIG. 1D i), a population of vesicles is captured with one or more capture agents against general vesicle biomarkers (100). The captured vesicles are then labeled with detectors against cell-of-origin biomarkers (101) and/or disease specific biomarkers (102). If only cell-of-origin detectors are used (101), the biosignature used to characterize the phenotype (103) can include the general vesicle markers (100) and the cell-of-origin biomarkers (101). If only disease detectors are used (102), the biosignature used to characterize the phenotype (103) can include the general vesicle markers (100) and the disease biomarkers (102). Alternately, detectors are used to detect both cell-of-origin biomarkers (101) and disease specific biomarkers (102). In this case, the biosignature used to characterize the phenotype (103) can include the general vesicle markers (100), the cell-of-origin biomarkers (101) and the disease biomarkers (102). The biomarkers combinations are selected to characterize the phenotype of interest and can be selected from the biomarkers and phenotypes described herein, e.g., in Tables 2 or 3.

In the scheme shown in FIG. 1D ii), a population of vesicles is captured with one or more capture agents against cell-of-origin biomarkers (110) and/or disease biomarkers (111). The captured vesicles are then detected using detectors against general vesicle biomarkers (112). If only cell-of-origin capture agents are used (110), the biosignature used to characterize the phenotype (113) can include the cell-of-origin biomarkers (110) and the general vesicle markers (112). If only disease biomarker capture agents are used (111), the biosignature used to characterize the phenotype (113) can include the disease biomarkers (111) and the general vesicle biomarkers (112). Alternately, capture agents to one or more cell-of-origin biomarkers (110) and one or more disease specific biomarkers (111) are used to capture vesicles. In this case, the biosignature used to characterize the phenotype (113) can include the cell-of-origin biomarkers (110), the disease biomarkers (111), and the general vesicle markers (113). The biomarkers combinations are selected to characterize the phenotype of interest and can be selected from the biomarkers and phenotypes described herein.

The methods of the invention comprise capture and detection of microvesicles of interest using any combination of useful biomarkers. For example, a microvesicle population can be captured using one or more binding agent to any desired combination of cell of origin, disease specific, or general vesicle markers. The captured microvesicles can then be detected using one or more binding agent to any desired combination of cell of origin, disease specific, or general vesicle markers. FIG. 1E represents a flow diagram of such configurations. Any one or more of a cell-of-origin biomarker (140), disease biomarkers (141), and general vesicle biomarker (142) is used to capture a microvesicle population. Thereafter, any one or more of a cell-of-origin biomarker (143), disease biomarkers (144), and general vesicle biomarker (145) is used to detect the captured microvesicle population. The biosignature of captured and detected microvesicles is then used to characterize a phenotype. The biomarkers combinations are selected to characterize the phenotype of interest and can be selected from the biomarkers and phenotypes described herein.

A microvesicle payload molecule can be assessed as a member of a biosignature panel. A payload molecule comprises any of the biological entities contained within a cell, cell fragment or vesicle membrane. These entities include without limitation nucleic acids, e.g., mRNA, microRNA, or DNA fragments; protein, e.g., soluble and membrane associated proteins; carbohydrates; lipids; metabolites; and various small molecules, e.g., hormones. The payload can be part of the cellular milieu that is encapsulated as a vesicle is formed in the cellular environment. In some embodiments of the invention, the payload is analyzed in addition to detecting vesicle surface antigens. Specific populations of vesicles can be captured as described above then the payload in the captured vesicles can be used to characterize a phenotype. For example, vesicles captured on a substrate can be further isolated to assess the payload therein. Alternately, the vesicles in a sample are detected and sorted without capture. The vesicles so detected can be further isolated to assess the payload therein. In an embodiment, vesicle populations are sorted by flow cytometry and the payload in the sorted vesicles is analyzed. In the scheme shown in FIG. 1F iii), a population of vesicles is captured and/or detected (120) using one or more of cell-of-origin biomarkers (120), disease biomarkers (121), and/or general vesicle markers (122). The payload of the isolated vesicles is assessed (123). A biosignature detected within the payload can be used to characterize a phenotype (124). In a non-limiting example, a vesicle population can be analyzed in a plasma sample from a patient using antibodies against one or more vesicle antigens of interest. The antibodies can be capture antibodies which are tethered to a substrate to isolate a desired vesicle population. Alternately, the antibodies can be directly labeled and the labeled vesicles isolated by sorting with flow cytometry. The presence or level of microRNA or mRNA extracted from the isolated vesicle population can be used to detect a biosignature. The biosignature is then used to diagnose, prognose or theranose the patient.

In other embodiments, vesicle or cellular payload is analyzed in a population (e.g., cells or vesicles) without first capturing or detected subpopulations of vesicles. For example, a cellular or extracellular vesicle population can be generally isolated from a sample using centrifugation, filtration, chromatography, or other techniques as described herein and known in the art. The payload of such sample components can be analyzed thereafter to detect a biosignature and characterize a phenotype. In the scheme shown in FIG. 1F v), a population of vesicles is isolated (130) and the payload of the isolated vesicles is assessed (131). A biosignature detected within the payload can be used to characterize a phenotype (132). In a non-limiting example, a vesicle population is isolated from a plasma sample from a patient using size exclusion and membrane filtration. The presence or level of microRNA or mRNA extracted from the vesicle population is used to detect a biosignature. The biosignature is then used to diagnose, prognose or theranose the patient.

The biomarkers used to detect a vesicle population can be selected to detect a microvesicle population of interest, e.g., a population of vesicles that provides a diagnosis, prognosis or theranosis of a selected condition or disease, including but not limited to a cancer, a premalignant condition, an inflammatory disease, an immune disease, an autoimmune disease or disorder, a cardiovascular disease or disorder, neurological disease or disorder, infectious disease or pain. See Section “Phenotypes” herein for more detail. In an embodiment, the biomarkers are selected from the group consisting of EpCam (epithelial cell adhesion molecule), CD9 (tetraspanin CD9 molecule), PCSA (prostate cell specific antigen, see Rokhlin et al., 5E10: a prostate-specific surface-reactive monoclonal antibody. Cancer Lett. 1998 131:129-36), CD63 (tetraspanin CD63 molecule), CD81 (tetraspanin CD81 molecule), PSMA (FOLH1, folate hydrolase (prostate-specific membrane antigen) 1), B7H3 (CD276 molecule), PSCA (prostate stem cell antigen), ICAM (intercellular adhesion molecule), STEAP (STEAP1, six transmembrane epithelial antigen of the prostate 1), KLK2 (kallikrein-related peptidase 2), SSX2 (synovial sarcoma, X breakpoint 2), SSX4 (synovial sarcoma, X breakpoint 4), PBP (prostatic binding protein), SPDEF (SAM pointed domain containing ets transcription factor), EGFR (epidermal growth factor receptor), and a combination thereof. One or more of these markers can provide a biosignature for a specific condition, such as to detect a cancer, including without limitation a carcinoma, a prostate cancer, a breast cancer, a lung cancer, a colorectal cancer, an ovarian cancer, melanoma, a brain cancer, or other type of cancer as disclosed herein. In an embodiment, a binding agent to one or more of these markers is used to capture a microvesicle population, and an aptamer of the invention is used to assist in detection of the capture vesicles as described herein. In other embodiments, an aptamer of the invention is used to capture a microvesicle population, and a binding agent to one or more of these markers is used to assist in detection of the capture vesicles as described herein. The binding agents can be any useful binding agent as disclosed herein or known in the art, e.g., antibodies or aptamers.

The methods of characterizing a phenotype can employ a combination of techniques to assess a component or population of components present in a biological sample of interest. For example, an aptamer of the invention can be used to assess a single cell, or a single extracellular vesicle or a population of cells or population of vesicles. A sample may be split into various aliquots, where each is analyzed separately. For example, protein content of one or more aliquot is determined and microRNA content of one or more other aliquot is determined. The protein content and microRNA content can be combined to characterize a phenotype. In another embodiment, a component present in a biological sample of interest is isolated and the payload therein is assessed (e.g., capture a population of subpopulation of vesicles using an aptamer of the invention and further assess nucleic acid or proteins present in the isolated vesicles).

In one embodiment, a population of vesicles with a given surface marker can be isolated by using a binding agent to a microvesicle surface marker. See, e.g., FIGS. 1A, 1B. The binding agent can be an aptamer that was identified to target the microvesicle surface marker using to the methods of the invention. The isolated vesicles is assessed for additional biomarkers such as surface content or payload, which can be contemporaneous to detection of the aptamer-specific target or the assessment of additional biomarkers can be before or subsequent to aptamer-specific target detection.

A biosignature can be detected qualitatively or quantitatively by detecting a presence, level or concentration of a circulating biomarker, e.g., a microRNA, protein, vesicle or other biomarker, as disclosed herein. These biosignature components can be detected using a number of techniques known to those of skill in the art. For example, a biomarker can be detected by microarray analysis, polymerase chain reaction (PCR) (including PCR-based methods such as real time polymerase chain reaction (RT-PCR), quantitative real time polymerase chain reaction (Q-PCR/qPCR) and the like), hybridization with allele-specific probes, enzymatic mutation detection, ligation chain reaction (LCR), oligonucleotide ligation assay (OLA), flow-cytometric heteroduplex analysis, chemical cleavage of mismatches, mass spectrometry, nucleic acid sequencing, single strand conformation polymorphism (SSCP), denaturing gradient gel electrophoresis (DGGE), temperature gradient gel electrophoresis (TGGE), restriction fragment polymorphisms, serial analysis of gene expression (SAGE), or combinations thereof. A biomarker, such as a nucleic acid, can be amplified prior to detection. A biomarker can also be detected by immunoassay, immunoblot, immunoprecipitation, enzyme-linked immunosorbent assay (ELISA; EIA), radioimmunoassay (RIA), flow cytometry, or electron microscopy (EM).

Biosignatures can be detected using aptamers of the invention that function as either as capture agents and detection agents, as described herein. A capture agent can comprise an antibody, aptamer or other entity which recognizes a biomarker and can be used for capturing the biomarker. Biomarkers that can be captured include circulating biomarkers, e.g., a protein, nucleic acid, lipid or biological complex in solution in a bodily fluid. Similarly, the capture agent can be used for capturing a vesicle. A detection agent can comprise an antibody or other entity which recognizes a biomarker and can be used for detecting the biomarker vesicle, or which recognizes a vesicle and is useful for detecting a vesicle. In some embodiments, the detection agent is labeled and the label is detected, thereby detecting the biomarker or vesicle. The detection agent can be a binding agent, e.g., an antibody or aptamer. In other embodiments, the detection agent comprises a small molecule such as a membrane protein labeling agent. See, e.g., the membrane protein labeling agents disclosed in Alroy et al., US. Patent Publication US 2005/0158708. In an embodiment, vesicles are isolated or captured as described herein, and one or more membrane protein labeling agent is used to detect the vesicles. In many cases, the antigen or other vesicle-moiety that is recognized by the capture and detection agents are interchangeable.

In a non-limiting embodiment, a vesicle having a cell-of-origin specific antigen on its surface and a cancer-specific antigen on its surface, is captured using a binding agent that is specific to a cells-specific antigen, e.g., by tethering the capture antibody or aptamer to a substrate, and then the vesicle is detected using a binding agent to a disease-specific antigen, e.g., by labeling the binding agent used for detection with a fluorescent dye and detecting the fluorescent radiation emitted by the dye.

It will be apparent to one of skill in the art that where the target molecule for a binding agent (such as an aptamer of the invention) is informative as to assessing a condition or disease, the same binding agent can be used to both capture a component comprising the target molecule (e.g., microvesicle surface antigen of interest) and also be modified to comprise a detectable label so as to detect the target molecule, e.g., binding agent₁-antigen-binding agent₂*, wherein the * signifies a detectable label; binding agent₂ and binding agent₂ may be the same binding agent or a different binding agent (e.g., same aptamer or different aptamer). In addition, binding agent₁ and binding agent₂ can be selected from wholly different categories of binding agents (e.g., antibody, aptamer, synthetic antibody, peptide-nucleic acid molecule, or any molecule that is configured to specifically bind to or associate with its target molecule). Such binding molecules can be selected solely based on their binding specificity for a target molecule.

Techniques of detecting biomarkers or capturing sample components using an aptamer of the invention include the use of a planar substrate such as an array (e.g., biochip or microarray), with molecules immobilized to the substrate as capture agents that facilitate the detection of a particular biosignature. The array can be provided as part of a kit for assaying one or more biomarkers. Additional examples of binding agents described above and useful in the compositions and methods of the invention are disclosed in International Patent Application Serial No. PCT/US2011/031479, entitled “Circulating Biomarkers for Disease” and filed Apr. 6, 2011, which application is incorporated by reference in its entirety herein. Aptamers of the invention can be included in an array for detection and diagnosis of diseases including presymptomatic diseases. In some embodiments, an array comprises a custom array comprising biomolecules selected to specifically identify biomarkers of interest. Customized arrays can be modified to detect biomarkers that increase statistical performance, e.g., additional biomolecules that identifies a biosignature which lead to improved cross-validated error rates in multivariate prediction models (e.g., logistic regression, discriminant analysis, or regression tree models). In some embodiments, customized array(s) are constructed to study the biology of a disease, condition or syndrome and profile biosignatures in defined physiological states. Markers for inclusion on the customized array be chosen based upon statistical criteria, e.g., having a desired level of statistical significance in differentiating between phenotypes or physiological states. In some embodiments, standard significance of p-value=0.05 is chosen to exclude or include biomolecules on the microarray. The p-values can be corrected for multiple comparisons. As an illustrative example, nucleic acids extracted from samples from a subject with or without a disease can be hybridized to a high density microarray that binds to thousands of gene sequences. Nucleic acids whose levels are significantly different between the samples with or without the disease can be selected as biomarkers to distinguish samples as having the disease or not. A customized array can be constructed to detect the selected biomarkers. In some embodiments, customized arrays comprise low density microarrays, which refer to arrays with lower number of addressable binding agents, e.g., tens or hundreds instead of thousands. Low density arrays can be formed on a substrate. In some embodiments, customizable low density arrays use PCR amplification in plate wells, e.g., TagMan® Gene Expression Assays (Applied Biosystems by Life Technologies Corporation, Carlsbad, Calif.).

An aptamer of the invention or other useful binding agent may be linked directly or indirectly to a solid surface or substrate. See, e.g., FIGS. 1A-1B. A solid surface or substrate can be any physically separable solid to which a binding agent can be directly or indirectly attached including, but not limited to, surfaces provided by microarrays and wells, particles such as beads, columns, optical fibers, wipes, glass and modified or functionalized glass, quartz, mica, diazotized membranes (paper or nylon), polyformaldehyde, cellulose, cellulose acetate, paper, ceramics, metals, metalloids, semiconductive materials, quantum dots, coated beads or particles, other chromatographic materials, magnetic particles; plastics (including acrylics, polystyrene, copolymers of styrene or other materials, polypropylene, polyethylene, polybutylene, polyurethanes, Teflon material, etc.), polysaccharides, nylon or nitrocellulose, resins, silica or silica-based materials including silicon and modified silicon, carbon, metals, inorganic glasses, plastics, ceramics, conducting polymers (including polymers such as polypyrole and polyindole); micro or nanostructured surfaces such as nucleic acid tiling arrays, nanotube, nanowire, or nanoparticulate decorated surfaces; or porous surfaces or gels such as methacrylates, acrylamides, sugar polymers, cellulose, silicates, or other fibrous or stranded polymers. In addition, as is known the art, the substrate may be coated using passive or chemically-derivatized coatings with any number of materials, including polymers, such as dextrans, acrylamides, gelatins or agarose. Such coatings can facilitate the use of the array with a biological sample.

As provided in the examples, below, an aptamer or other useful binding agent can be conjugated to a detectable entity or label. Appropriate labels include without limitation a magnetic label, a fluorescent moiety, an enzyme, a chemiluminescent probe, a metal particle, a non-metal colloidal particle, a polymeric dye particle, a pigment molecule, a pigment particle, an electrochemically active species, semiconductor nanocrystal or other nanoparticles including quantum dots or gold particles, fluorophores, quantum dots, or radioactive labels. Protein labels include green fluorescent protein (GFP) and variants thereof (e.g., cyan fluorescent protein and yellow fluorescent protein); and luminescent proteins such as luciferase, as described below. Radioactive labels include without limitation radioisotopes (radionuclides), such as ³H, ¹¹C, ¹⁴C, ¹⁸F, ³²P, ³⁵S, ⁶⁴Cu, ⁶⁸Ga, ⁸⁶Y, ⁹⁹Tc, ¹¹¹In, ¹²³I, ¹²⁴I, ¹²⁵I, ¹³¹I, ¹³³Xe, ¹⁷⁷Lu, ²¹¹At, or ²¹³Bi. Fluorescent labels include without limitation a rare earth chelate (e.g., europium chelate), rhodamine; fluorescein types including without limitation FITC, 5-carboxyfluorescein, 6-carboxy fluorescein; a rhodamine type including without limitation TAMRA; dansyl; Lissamine; cyanines; phycoerythrins; Texas Red; Cy3, Cy5, dapoxyl, NBD, Cascade Yellow, dansyl, PyMPO, pyrene, 7-diethylaminocoumarin-3-carboxylic acid and other coumarin derivatives, Marina Blue™, Pacific Blue™, Cascade Blue™, 2-anthracenesulfonyl, PyMPO, 3,4,9,10-perylene-tetracarboxylic acid, 2,7-difluorofluorescein (Oregon Green™ 488-X), 5-carboxyfluorescein, Texas Red™-X, Alexa Fluor 430, 5-carboxytetramethylrhodamine(5-TAMRA), 6-carboxytetramethylrhodamine(6-TAMRA), BODIPY FL, bimane, and Alexa Fluor 350, 405, 488, 500, 514, 532, 546, 555, 568, 594, 610, 633, 647, 660, 680, 700, and 750, and derivatives thereof, among many others. See, e.g., “The Handbook—A Guide to Fluorescent Probes and Labeling Technologies,” Tenth Edition, available on the internet at probes (dot) invitrogen (dot) com/handbook. The fluorescent label can be one or more of FAM, dRHO, 5-FAM, 6FAM, dR6G, JOE, HEX, VIC, TET, dTAMRA, TAMRA, NED, dROX, PET, BHQ, Gold540 and LIZ.

Using conventional techniques, an aptamer can be directly or indirectly labeled, e.g., the label is attached to the aptamer through biotin-streptavidin (e.g., synthesize a biotinylated aptamer, which is then capable of binding a streptavidin molecule that is itself conjugated to a detectable label; non-limiting example is streptavidin, phycoerythrin conjugated (SAPE)). Methods for chemical coupling using multiple step procedures include biotinylation, coupling of trinitrophenol (TNP) or digoxigenin using for example succinimide esters of these compounds. Biotinylation can be accomplished by, for example, the use of D-biotinyl-N-hydroxysuccinimide. Succinimide groups react effectively with amino groups at pH values above 7, and preferentially between about pH 8.0 and about pH 8.5. Alternatively, an aptamer is not labeled, but is later contacted with a second antibody that is labeled after the first antibody is bound to an antigen of interest.

Various enzyme-substrate labels may also be used in conjunction with a composition or method of the invention. Such enzyme-substrate labels are available commercially (e.g., U.S. Pat. No. 4,275,149). The enzyme generally catalyzes a chemical alteration of a chromogenic substrate that can be measured using various techniques. For example, the enzyme may catalyze a color change in a substrate, which can be measured spectrophotometrically. Alternatively, the enzyme may alter the fluorescence or chemiluminescence of the substrate. Examples of enzymatic labels include luciferases (e.g., firefly luciferase and bacterial luciferase; U.S. Pat. No. 4,737,456), luciferin, 2,3-dihydrophthalazinediones, malate dehydrogenase, urease, peroxidase such as horseradish peroxidase (HRP), alkaline phosphatase (AP), β-galactosidase, glucoamylase, lysozyme, saccharide oxidases (e.g., glucose oxidase, galactose oxidase, and glucose-6-phosphate dehydrogenase), heterocyclic oxidases (such as uricase and xanthine oxidase), lactoperoxidase, microperoxidase, and the like. Examples of enzyme-substrate combinations include, but are not limited to, horseradish peroxidase (HRP) with hydrogen peroxidase as a substrate, wherein the hydrogen peroxidase oxidizes a dye precursor (e.g., orthophenylene diamine (OPD) or 3,3′,5,5′-tetramethylbenzidine hydrochloride (TMB)); alkaline phosphatase (AP) with para-nitrophenyl phosphate as chromogenic substrate; and β-D-galactosidase (β-D-Gal) with a chromogenic substrate (e.g., p-nitrophenyl-β-D-galactosidase) or fluorogenic substrate 4-methylumbelliferyl-β-D-galactosidase.

Aptamer(s) can be linked to a substrate such as a planar substrate. A planar array generally contains addressable locations (e.g., pads, addresses, or micro-locations) of biomolecules in an array format. The size of the array will depend on the composition and end use of the array. Arrays can be made containing from 2 different molecules to many thousands. Generally, the array comprises from two to as many as 100,000 or more molecules, depending on the end use of the array and the method of manufacture. A microarray for use with the invention comprises at least one biomolecule that identifies or captures a biomarker present in a biosignature of interest, e.g., a microRNA or other biomolecule or vesicle that makes up the biosignature. In some arrays, multiple substrates are used, either of different or identical compositions. Accordingly, planar arrays may comprise a plurality of smaller substrates.

The present invention can make use of many types of arrays for detecting a biomarker, e.g., a biomarker associated with a biosignature of interest. Useful arrays or microarrays include without limitation DNA microarrays, such as cDNA microarrays, oligonucleotide microarrays and SNP microarrays, microRNA arrays, protein microarrays, antibody microarrays, tissue microarrays, cellular microarrays (also called transfection microarrays), chemical compound microarrays, and carbohydrate arrays (glycoarrays). These arrays are described in more detail above. In some embodiments, microarrays comprise biochips that provide high-density immobilized arrays of recognition molecules (e.g., aptamers or antibodies), where biomarker binding is monitored indirectly (e.g., via fluorescence).

An array or microarray that can be used to detect one or more biomarkers of a biosignature and comprising one or more aptamers can be made according to the methods described in U.S. Pat. Nos. 6,329,209; 6,365,418; 6,406,921; 6,475,808; and 6,475,809, and U.S. patent application Ser. No. 10/884,269, each of which is herein incorporated by reference in its entirety. Custom arrays to detect specific selections of sets of biomarkers described herein can be made using the methods described in these patents. Commercially available microarrays can also be used to carry out the methods of the invention, including without limitation those from Affymetrix (Santa Clara, Calif.), Illumina (San Diego, Calif.), Agilent (Santa Clara, Calif.), Exiqon (Denmark), or Invitrogen (Carlsbad, Calif.). Custom and/or commercial arrays include arrays for detection proteins, nucleic acids, and other biological molecules and entities (e.g., cells, vesicles, virii) as described herein.

In some embodiments, multiple capture molecules are disposed on an array, e.g., proteins, peptides or additional nucleic acid molecules. In certain embodiments, the proteins are immobilized using methods and materials that minimize the denaturing of the proteins, that minimize alterations in the activity of the proteins, or that minimize interactions between the protein and the surface on which they are immobilized. The capture molecules can comprise one or more aptamer of the invention.

Array surfaces useful may be of any desired shape, form, or size. Non-limiting examples of surfaces include chips, continuous surfaces, curved surfaces, flexible surfaces, films, plates, sheets, or tubes. Surfaces can have areas ranging from approximately a square micron to approximately 500 cm². The area, length, and width of surfaces may be varied according to the requirements of the assay to be performed. Considerations may include, for example, ease of handling, limitations of the material(s) of which the surface is formed, requirements of detection systems, requirements of deposition systems (e.g., arrayers), or the like.

In certain embodiments, it is desirable to employ a physical means for separating groups or arrays of binding islands or immobilized biomolecules: such physical separation facilitates exposure of different groups or arrays to different solutions of interest. Therefore, in certain embodiments, arrays are situated within microwell plates having any number of wells. In such embodiments, the bottoms of the wells may serve as surfaces for the formation of arrays, or arrays may be formed on other surfaces and then placed into wells. In certain embodiments, such as where a surface without wells is used, binding islands may be formed or molecules may be immobilized on a surface and a gasket having holes spatially arranged so that they correspond to the islands or biomolecules may be placed on the surface. Such a gasket is preferably liquid tight. A gasket may be placed on a surface at any time during the process of making the array and may be removed if separation of groups or arrays is no longer necessary.

In some embodiments, the immobilized molecules can bind to one or more biomarkers or vesicles present in a biological sample contacting the immobilized molecules. In some embodiments, the immobilized molecules modify or are modified by molecules present in the one or more vesicles contacting the immobilized molecules. Contacting the sample typically comprises overlaying the sample upon the array.

Modifications or binding of molecules in solution or immobilized on an array can be detected using detection techniques known in the art. Examples of such techniques include immunological techniques such as competitive binding assays and sandwich assays; fluorescence detection using instruments such as confocal scanners, confocal microscopes, or CCD-based systems and techniques such as fluorescence, fluorescence polarization (FP), fluorescence resonant energy transfer (FRET), total internal reflection fluorescence (TIRF), fluorescence correlation spectroscopy (FCS); colorimetric/spectrometric techniques; surface plasmon resonance, by which changes in mass of materials adsorbed at surfaces are measured; techniques using radioisotopes, including conventional radioisotope binding and scintillation proximity assays (SPA); mass spectroscopy, such as matrix-assisted laser desorption/ionization mass spectroscopy (MALDI) and MALDI-time of flight (TOF) mass spectroscopy; ellipsometry, which is an optical method of measuring thickness of protein films; quartz crystal microbalance (QCM), a very sensitive method for measuring mass of materials adsorbing to surfaces; scanning probe microscopies, such as atomic force microscopy (AFM), scanning force microscopy (SFM) or scanning electron microscopy (SEM); and techniques such as electrochemical, impedance, acoustic, microwave, and IR/Raman detection. See, e.g., Mere L, et al., “Miniaturized FRET assays and microfluidics: key components for ultra-high-throughput screening,” Drug Discovery Today 4(8):363-369 (1999), and references cited therein; Lakowicz J R, Principles of Fluorescence Spectroscopy, 2nd Edition, Plenum Press (1999), or Jain K K: Integrative Omics, Pharmacoproteomics, and Human Body Fluids. In: Thongboonkerd V, ed., ed. Proteomics of Human Body Fluids: Principles, Methods and Applications. Volume 1: Totowa, N.J.: Humana Press, 2007, each of which is herein incorporated by reference in its entirety.

Microarray technology can be combined with mass spectroscopy (MS) analysis and other tools. Electrospray interface to a mass spectrometer can be integrated with a capillary in a microfluidics device. For example, one commercially available system contains eTag reporters that are fluorescent labels with unique and well-defined electrophoretic mobilities; each label is coupled to biological or chemical probes via cleavable linkages. The distinct mobility address of each eTag reporter allows mixtures of these tags to be rapidly deconvoluted and quantitated by capillary electrophoresis. This system allows concurrent gene expression, protein expression, and protein function analyses from the same sample Jain K K: Integrative Omics, Pharmacoproteomics, and Human Body Fluids. In: Thongboonkerd V, ed., ed. Proteomics of Human Body Fluids: Principles, Methods and Applications. Volume 1: Totowa, N.J.: Humana Press, 2007, which is herein incorporated by reference in its entirety.

A biochip can include components for a microfluidic or nanofluidic assay. A microfluidic device can be used for isolating or analyzing biomarkers, such as determining a biosignature. Microfluidic systems allow for the miniaturization and compartmentalization of one or more processes for isolating, capturing or detecting a vesicle, detecting a microRNA, detecting a circulating biomarker, detecting a biosignature, and other processes. The microfluidic devices can use one or more detection reagents in at least one aspect of the system, and such a detection reagent can be used to detect one or more biomarkers. In one embodiment, the device detects a biomarker on an isolated or bound vesicle. Various probes, antibodies, proteins, or other binding agents can be used to detect a biomarker within the microfluidic system. The detection agents may be immobilized in different compartments of the microfluidic device or be entered into a hybridization or detection reaction through various channels of the device.

A vesicle in a microfluidic device can be lysed and its contents detected within the microfluidic device, such as proteins or nucleic acids, e.g., DNA or RNA such as miRNA or mRNA. The nucleic acid may be amplified prior to detection, or directly detected, within the microfluidic device. Thus microfluidic system can also be used for multiplexing detection of various biomarkers. In an embodiment, vesicles are captured within the microfluidic device, the captured vesicles are lysed, and a biosignature of microRNA from the vesicle payload is determined. The biosignature can further comprise the capture agent used to capture the vesicle.

Novel nanofabrication techniques are opening up the possibilities for biosensing applications that rely on fabrication of high-density, precision arrays, e.g., nucleotide-based chips and protein arrays otherwise known as heterogeneous nanoarrays. Nanofluidics allows a further reduction in the quantity of fluid analyte in a microchip to nanoliter levels, and the chips used here are referred to as nanochips. See, e.g., Unger M et al., Biotechniques 1999; 27(5):1008-14, Kartalov E P et al., Biotechniques 2006; 40(1):85-90, each of which are herein incorporated by reference in their entireties. Commercially available nanochips currently provide simple one step assays such as total cholesterol, total protein or glucose assays that can be run by combining sample and reagents, mixing and monitoring of the reaction. Gel-free analytical approaches based on liquid chromatography (LC) and nanoLC separations (Cutillas et al. Proteomics, 2005; 5:101-112 and Cutillas et al., Mol Cell Proteomics 2005; 4:1038-1051, each of which is herein incorporated by reference in its entirety) can be used in combination with the nanochips.

An array suitable for identifying a disease, condition, syndrome or physiological status can be included in a kit. A kit can include, an aptamer of the invention, including as non-limiting examples, one or more reagents useful for preparing molecules for immobilization onto binding islands or areas of an array, reagents useful for detecting binding of a vesicle to immobilized molecules, and instructions for use.

Further provided herein is a rapid detection device that facilitates the detection of a particular biosignature in a biological sample. The device can integrate biological sample preparation with polymerase chain reaction (PCR) on a chip. The device can facilitate the detection of a particular biosignature of a vesicle in a biological sample, and an example is provided as described in Pipper et al., Angewandte Chemie, 47(21), p. 3900-3904 (2008), which is herein incorporated by reference in its entirety. A biosignature can be incorporated using micro-/nano-electrochemical system (MEMS/NEMS) sensors and oral fluid for diagnostic applications as described in Li et al., Adv Dent Res 18(1): 3-5 (2005), which is herein incorporated by reference in its entirety.

In addition to acting as binding agents for a target of interest in an assay, certain aptamers of the invention, e.g., functional group binding aptamers and/or blocking aptamers, can be used to enhance the performance of various biomarker detection techniques disclosed herein or known in the art. As described further below, such aptamers can be used in an assay that makes use of a substrate, wherein the aptamers mitigate non-specific binding to the substrate.

Particle Assays

As an alternative to planar arrays, assays using particles or microspheres, such as bead based assays are also capable of use with an aptamer of the invention. Binding agents such as aptamers and antibodies are easily conjugated with commercially available beads. See, e.g., Srinivas et al. Anal. Chem. 2011 Oct. 21, Aptamer functionalized Microgel Particles for Protein Detection; See also, review article on aptamers as therapeutic and diagnostic agents, Brody and Gold, Rev. Mol. Biotech. 2000, 74:5-13.

Multiparametric assays or other high throughput detection assays using bead coatings with cognate ligands and reporter molecules with specific activities consistent with high sensitivity automation can be used. In a bead based assay system, a binding agent for a biomarker or vesicle, such as a capture agent (e.g. capture antibody), can be immobilized on an addressable microsphere. Each binding agent for each individual binding assay can be coupled to a distinct type of microsphere (i.e., microbead) and the assay reaction takes place on the surface of the microsphere, such as depicted in FIG. 1B. A binding agent for a vesicle can be a capture antibody coupled to a bead. Dyed microspheres with discrete fluorescence intensities are loaded separately with their appropriate binding agent or capture probes. The different bead sets carrying different binding agents can be pooled as necessary to generate custom bead arrays. Bead arrays are then incubated with the sample in a single reaction vessel to perform the assay. The bead conjugated vesicles can be used to enrich for aptamers the bind the microvesicles. See Examples.

Bead-based assays can also be used with one or more aptamers of the invention. A bead substrate can provide a platform for attaching one or more binding agents, including aptamer(s). For multiplexing, multiple different bead sets (e.g., Illumina, Luminex) can have different binding agents (specific to different target molecules). For example, a bead can be conjugated to a binding agent, e.g., an aptamer of the invention, used to detect the presence (quantitatively or qualitatively) of an antigen of interest, or it can also be used to isolate a component present in a selected biological sample (e.g., cell, cell-fragment or vesicle comprising the target molecule to which the aptamer is configured to bind or associate). Any molecule of organic origin can be successfully conjugated to a polystyrene bead through use of commercially available kits.

One or more aptamers of the invention can be used with any bead based substrate, including but not limited to magnetic capture method, fluorescence activated cell sorting (FACS) or laser cytometry. Magnetic capture methods can include, but are not limited to, the use of magnetically activated cell sorter (MACS) microbeads or magnetic columns. Examples of bead or particle based methods that can be modified to use an aptamer of the invention include methods and bead systems described in U.S. Pat. Nos. 4,551,435, 4,795,698, 4,925,788, 5,108,933, 5,186,827, 5,200,084 or 5,158,871; 7,399,632; 8,124,015; 8,008,019; 7,955,802; 7,445,844; 7,274,316; 6,773,812; 6,623,526; 6,599,331; 6,057,107; 5,736,330; international patent application no. PCT/US2012/42519; PCT/US1993/04145.

Flow Cytometry

Isolation or detection of circulating biomarkers, e.g., protein antigens, from a biological sample, or of the biomarker-comprising cells, cell fragments or vesicles may also be achieved using an aptamer of the invention in a cytometry process. As a non-limiting example, aptamers of the invention can be used in an assay comprising using a particle such as a bead or microsphere The invention provides aptamers as binding agents, which may be conjugated to the particle. Flow cytometry can be used for sorting microscopic particles suspended in a stream of fluid. As particles pass through they can be selectively charged and on their exit can be deflected into separate paths of flow. It is therefore possible to separate populations from an original mix, such as a biological sample, with a high degree of accuracy and speed. Flow cytometry allows simultaneous multiparametric analysis of the physical and/or chemical characteristics of single cells flowing through an optical/electronic detection apparatus. A beam of light, usually laser light, of a single frequency (color) is directed onto a hydrodynamically focused stream of fluid. A number of detectors are aimed at the point where the stream passes through the light beam; one in line with the light beam (Forward Scatter or FSC) and several perpendicular to it (Side Scatter or SSC) and one or more fluorescent detectors.

Each suspended particle passing through the beam scatters the light in some way, and fluorescent chemicals in the particle may be excited into emitting light at a lower frequency than the light source. This combination of scattered and fluorescent light is picked up by the detectors, and by analyzing fluctuations in brightness at each detector (one for each fluorescent emission peak), it is possible to deduce various facts about the physical and chemical structure of each individual particle. FSC correlates with the cell size and SSC depends on the inner complexity of the particle, such as shape of the nucleus, the amount and type of cytoplasmic granules or the membrane roughness. Some flow cytometers have eliminated the need for fluorescence and use only light scatter for measurement.

Flow cytometers can analyze several thousand particles every second in “real time” and can actively separate out and isolate particles having specified properties. They offer high-throughput automated quantification, and separation, of the set parameters for a high number of single cells during each analysis session. Flow cytometers can have multiple lasers and fluorescence detectors, allowing multiple labels to be used to more precisely specify a target population by their phenotype. Thus, a flow cytometer, such as a multicolor flow cytometer, can be used to detect one or more vesicles with multiple fluorescent labels or colors. In some embodiments, the flow cytometer can also sort or isolate different vesicle populations, such as by size or by different markers.

The flow cytometer may have one or more lasers, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more lasers. In some embodiments, the flow cytometer can detect more than one color or fluorescent label, such as at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 different colors or fluorescent labels. For example, the flow cytometer can have at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 fluorescence detectors.

Examples of commercially available flow cytometers that can be used to detect or analyze one or more vesicles, to sort or separate different populations of vesicles, include, but are not limited to the MoFlo™ XDP Cell Sorter (Beckman Coulter, Brea, Calif.), MoFlo™ Legacy Cell Sorter (Beckman Coulter, Brea, Calif.), BD FACSAria™ Cell Sorter (BD Biosciences, San Jose, Calif.), BD™ LSRII (BD Biosciences, San Jose, Calif.), and BD FACSCalibur™ (BD Biosciences, San Jose, Calif.). Use of multicolor or multi-fluor cytometers can be used in multiplex analysis of vesicles, as further described below. In some embodiments, the flow cytometer can sort, and thereby collect or sort more than one population of vesicles based one or more characteristics. For example, two populations of vesicles differ in size, such that the vesicles within each population have a similar size range and can be differentially detected or sorted. In another embodiment, two different populations of vesicles are differentially labeled.

The data resulting from flow-cytometers can be plotted in 1 dimension to produce histograms or seen in 2 dimensions as dot plots or in 3 dimensions with newer software. The regions on these plots can be sequentially separated by a series of subset extractions which are termed gates. Specific gating protocols exist for diagnostic and clinical purposes especially in relation to hematology. The plots are often made on logarithmic scales. Because different fluorescent dye's emission spectra overlap, signals at the detectors have to be compensated electronically as well as computationally. Fluorophores for labeling biomarkers may include those described in Ormerod, Flow Cytometry 2nd ed., Springer-Verlag, New York (1999), and in Nida et al., Gynecologic Oncology 2005; 4 889-894 which is incorporated herein by reference. In a multiplexed assay, including but not limited to a flow cytometry assay, one or more different target molecules can be assessed. In some embodiments, at least one of the target molecules is a biomarker, e.g., a microvesicle surface antigen, assessed using an aptamer of the invention.

Microfluidics

One or more aptamer of the invention can be conjugated to or otherwise disposed on any useful planar or bead substrate. In one aspect of the invention one or more aptamer of the invention is disposed on a microfluidic device, thereby facilitating assessing, characterizing or isolating a component of a biological sample comprising a polypeptide antigen of interest or a functional fragment thereof. For example, the circulating antigen or a cell, cell fragment or cell-derived vesicles comprising the antigen can be assessed using one or more aptamers of the invention (alternatively along with additional binding agents). Microfluidic devices, which may also be referred to as “lab-on-a-chip” systems, biomedical micro-electro-mechanical systems (bioMEMs), or multicomponent integrated systems, can be used for isolating and analyzing a vesicle. Such systems miniaturize and compartmentalize processes that allow for binding of vesicles, detection of biosignatures, and other processes.

A microfluidic device can also be used for isolation of a vesicle through size differential or affinity selection. For example, a microfluidic device can use one more channels for isolating a vesicle from a biological sample based on size or by using one or more binding agents for isolating a vesicle from a biological sample. A biological sample can be introduced into one or more microfluidic channels, which selectively allows the passage of a vesicle. The selection can be based on a property of the vesicle, such as the size, shape, deformability, or biosignature of the vesicle.

In one embodiment, a heterogeneous population of vesicles can be introduced into a microfluidic device, and one or more different homogeneous populations of vesicles can be obtained. For example, different channels can have different size selections or binding agents to select for different vesicle populations. Thus, a microfluidic device can isolate a plurality of vesicles wherein at least a subset of the plurality of vesicles comprises a different biosignature from another subset of the plurality of vesicles. For example, the microfluidic device can isolate at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, or 100 different subsets of vesicles, wherein each subset of vesicles comprises a different biosignature.

In some embodiments, the microfluidic device can comprise one or more channels that permit further enrichment or selection of a vesicle. A population of vesicles that has been enriched after passage through a first channel can be introduced into a second channel, which allows the passage of the desired vesicle or vesicle population to be further enriched, such as through one or more binding agents present in the second channel.

Array-based assays and bead-based assays can be used with microfluidic device. For example, the binding agent can be coupled to beads and the binding reaction between the beads and vesicle can be performed in a microfluidic device. Multiplexing can also be performed using a microfluidic device. Different compartments can comprise different binding agents for different populations of vesicles, where each population is of a different cell-of-origin specific vesicle population. In one embodiment, each population has a different biosignature. The hybridization reaction between the microsphere and vesicle can be performed in a microfluidic device and the reaction mixture can be delivered to a detection device. The detection device, such as a dual or multiple laser detection system can be part of the microfluidic system and can use a laser to identify each bead or microsphere by its color-coding, and another laser can detect the hybridization signal associated with each bead.

Any appropriate microfluidic device can be used in the methods of the invention. Examples of microfluidic devices that may be used, or adapted for use with vesicles, include but are not limited to those described in U.S. Pat. Nos. 7,591,936, 7,581,429, 7,579,136, 7,575,722, 7,568,399, 7,552,741, 7,544,506, 7,541,578, 7,518,726, 7,488,596, 7,485,214, 7,467,928, 7,452,713, 7,452,509, 7,449,096, 7,431,887, 7,422,725, 7,422,669, 7,419,822, 7,419,639, 7,413,709, 7,411,184, 7,402,229, 7,390,463, 7,381,471, 7,357,864, 7,351,592, 7,351,380, 7,338,637, 7,329,391, 7,323,140, 7,261,824, 7,258,837, 7,253,003, 7,238,324, 7,238,255, 7,233,865, 7,229,538, 7,201,881, 7,195,986, 7,189,581, 7,189,580, 7,189,368, 7,141,978, 7,138,062, 7,135,147, 7,125,711, 7,118,910, 7,118,661, 7,640,947, 7,666,361, 7,704,735; and International Patent Publication WO 2010/072410; each of which patents or applications are incorporated herein by reference in their entirety. Another example for use with methods disclosed herein is described in Chen et al., “Microfluidic isolation and transcriptome analysis of serum vesicles,” Lab on a Chip, Dec. 8, 2009 DOI: 10.1039/b916199f

Other microfluidic devices for use with the invention include devices comprising elastomeric layers, valves and pumps, including without limitation those disclosed in U.S. Pat. Nos. 5,376,252, 6,408,878, 6,645,432, 6,719,868, 6,793,753, 6,899,137, 6,929,030, 7,040,338, 7,118,910, 7,144,616, 7,216,671, 7,250,128, 7,494,555, 7,501,245, 7,601,270, 7,691,333, 7,754,010, 7,837,946; U.S. Patent Application Nos. 2003/0061687, 2005/0084421, 2005/0112882, 2005/0129581, 2005/0145496, 2005/0201901, 2005/0214173, 2005/0252773, 2006/0006067; and EP Patent Nos. 0527905 and 1065378; each of which application is herein incorporated by reference. In some instances, much or all of the devices are composed of elastomeric material. Certain devices are designed to conduct thermal cycling reactions (e.g., PCR) with devices that include one or more elastomeric valves to regulate solution flow through the device. The devices can comprise arrays of reaction sites thereby allowing a plurality of reactions to be performed. Thus, the devices can be used to assess circulating microRNAs in a multiplex fashion, including microRNAs isolated from vesicles. In an embodiment, the microfluidic device comprises (a) a first plurality of flow channels formed in an elastomeric substrate; (b) a second plurality of flow channels formed in the elastomeric substrate that intersect the first plurality of flow channels to define an array of reaction sites, each reaction site located at an intersection of one of the first and second flow channels; (c) a plurality of isolation valves disposed along the first and second plurality of flow channels and spaced between the reaction sites that can be actuated to isolate a solution within each of the reaction sites from solutions at other reaction sites, wherein the isolation valves comprise one or more control channels that each overlay and intersect one or more of the flow channels; and (d) means for simultaneously actuating the valves for isolating the reaction sites from each other. Various modifications to the basic structure of the device are envisioned within the scope of the invention. MicroRNAs can be detected in each of the reaction sites by using PCR methods. For example, the method can comprise the steps of the steps of: (i) providing a microfluidic device, the microfluidic device comprising: a first fluidic channel having a first end and a second end in fluid communication with each other through the channel; a plurality of flow channels, each flow channel terminating at a terminal wall; wherein each flow channel branches from and is in fluid communication with the first fluidic channel, wherein an aqueous fluid that enters one of the flow channels from the first fluidic channel can flow out of the flow channel only through the first fluidic channel; and, an inlet in fluid communication with the first fluidic channel, the inlet for introducing a sample fluid; wherein each flow channel is associated with a valve that when closed isolates one end of the flow channel from the first fluidic channel, whereby an isolated reaction site is formed between the valve and the terminal wall; a control channel; wherein each the valve is a deflectable membrane which is deflected into the flow channel associated with the valve when an actuating force is applied to the control channel, thereby closing the valve; and wherein when the actuating force is applied to the control channel a valve in each of the flow channels is closed, so as to produce the isolated reaction site in each flow channel; (ii) introducing the sample fluid into the inlet, the sample fluid filling the flow channels; (iii) actuating the valve to separate the sample fluid into the separate portions within the flow channels; (iv) amplifying the nucleic acid in the sample fluid; (v) analyzing the portions of the sample fluid to determine whether the amplifying produced the reaction. The sample fluid can contain an amplifiable nucleic acid target, e.g., a microRNA, and the conditions can be polymerase chain reaction (PCR) conditions, so that the reaction results in a PCR product being formed.

The microfluidic device can have one or more binding agents attached to a surface in a channel, or present in a channel. For example, the microchannel can have one or more capture agents, such as a capture agent for one or more general microvesicle antigen in Table 2 or a cell-of-origin or cancer related antigen in Table 3, including without limitation EpCam, CD9, PCSA, CD63, CD81, PSMA, B7H3, PSCA, ICAM, STEAP, KLK2, SSX2, SSX4, PBP, SPDEF, and EGFR. The capture agent may be an aptamer selected by the methods of the invention. The surface of the channel can also be contacted with a blocking aptamer of the invention. In one embodiment, a microchannel surface is treated with avidin and a capture agent, such as an antibody, that is biotinylated can be injected into the channel to bind the avidin. In other embodiments, the capture agents are present in chambers or other components of a microfluidic device. The capture agents can also be attached to beads that can be manipulated to move through the microfluidic channels. In one embodiment, the capture agents are attached to magnetic beads. The beads can be manipulated using magnets.

A biological sample can be flowed into the microfluidic device, or a microchannel, at rates such as at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, or 50 μl per minute, such as between about 1-50, 5-40, 5-30, 3-20 or 5-15 μl per minute. One or more vesicles can be captured and directly detected in the microfluidic device. Alternatively, the captured vesicle may be released and exit the microfluidic device prior to analysis. In another embodiment, one or more captured vesicles are lysed in the microchannel and the lysate can be analyzed, e.g., to examine payload within the vesicles. Lysis buffer can be flowed through the channel and lyse the captured vesicles. For example, the lysis buffer can be flowed into the device or microchannel at rates such as at least about a, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 26, 27, 28, 29, 30, 35, 40, 45, or 50 μl per minute, such as between about 1-50, 5-40, 10-30, 5-30 or 10-35 μl per minute. The lysate can be collected and analyzed, such as performing RT-PCR, PCR, mass spectrometry, Western blotting, or other assays, to detect one or more biomarkers of the vesicle.

Phenotypes

Disclosed herein are products and processes for characterizing a phenotype using the methods and compositions of the invention. The term “phenotype” as used herein can mean any trait or characteristic that is attributed to a biomarker profile that is identified using in part or in whole the compositions and/or methods of the invention. For example, a phenotype can be a diagnostic, prognostic or theranostic determination based on a characterized biomarker profile for a sample obtained from a subject. A phenotype can be any observable characteristic or trait of, such as a disease or condition, a stage of a disease or condition, susceptibility to a disease or condition, prognosis of a disease stage or condition, a physiological state, or response/potential response to therapeutics. A phenotype can result from a subject's genetic makeup as well as the influence of environmental factors and the interactions between the two, as well as from epigenetic modifications to nucleic acid sequences.

A phenotype in a subject can be characterized by obtaining a biological sample from a subject and analyzing the sample using the compositions and/or methods of the invention. For example, characterizing a phenotype for a subject or individual can include detecting a disease or condition (including pre-symptomatic early stage detecting), determining a prognosis, diagnosis, or theranosis of a disease or condition, or determining the stage or progression of a disease or condition. Characterizing a phenotype can include identifying appropriate treatments or treatment efficacy for specific diseases, conditions, disease stages and condition stages, predictions and likelihood analysis of disease progression, particularly disease recurrence, metastatic spread or disease relapse. A phenotype can also be a clinically distinct type or subtype of a condition or disease, such as a cancer or tumor. Phenotype determination can also be a determination of a physiological condition, or an assessment of organ distress or organ rejection, such as post-transplantation. The compositions and methods described herein allow assessment of a subject on an individual basis, which can provide benefits of more efficient and economical decisions in treatment.

In an aspect, the invention relates to the analysis of biomarkers such as microvesicles to provide a diagnosis, prognosis, and/or theranosis of a disease or condition. Theranostics includes diagnostic testing that provides the ability to affect therapy or treatment of a disease or disease state. Theranostics testing provides a theranosis in a similar manner that diagnostics or prognostic testing provides a diagnosis or prognosis, respectively. As used herein, theranostics encompasses any desired form of therapy related testing, including predictive medicine, personalized medicine, integrated medicine, pharmacodiagnostics and Dx/Rx partnering. Therapy related tests can be used to predict and assess drug response in individual subjects, i.e., to provide personalized medicine. Predicting a drug response can be determining whether a subject is a likely responder or a likely non-responder to a candidate therapeutic agent, e.g., before the subject has been exposed or otherwise treated with the treatment. Assessing a drug response can be monitoring a response to a drug, e.g., monitoring the subject's improvement or lack thereof over a time course after initiating the treatment. Therapy related tests are useful to select a subject for treatment who is particularly likely to benefit from the treatment or to provide an early and objective indication of treatment efficacy in an individual subject. Thus, analysis using the compositions and methods of the invention may indicate that treatment should be altered to select a more promising treatment, thereby avoiding the great expense of delaying beneficial treatment and avoiding the financial and morbidity costs of administering an ineffective drug(s).

Thus, the compositions and methods of the invention may help predict whether a subject is likely to respond to a treatment for a disease or disorder. Characterizating a phenotype includes predicting the responder/non-responder status of the subject, wherein a responder responds to a treatment for a disease and a non-responder does not respond to the treatment. Biomarkers such as microvesicles can be analyzed in the subject and compared against that of previous subjects that were known to respond or not to a treatment. If the biomarker profile in the subject more closely aligns with that of previous subjects that were known to respond to the treatment, the subject can be characterized, or predicted, as a responder to the treatment. Similarly, if the biomarker profile in the subject more closely aligns with that of previous subjects that did not respond to the treatment, the subject can be characterized, or predicted as a non-responder to the treatment. The treatment can be for any appropriate disease, disorder or other condition, including without limitation those disclosed herein.

The phenotype can comprise detecting the presence of or likelihood of developing a tumor, neoplasm, or cancer, or characterizing the tumor, neoplasm, or cancer (e.g., stage, grade, aggressiveness, likelihood of metastatis or recurrence, etc). Cancers that can be detected or assessed by methods or compositions described herein include, but are not limited to, breast cancer, ovarian cancer, lung cancer, colon cancer, hyperplastic polyp, adenoma, colorectal cancer, high grade dysplasia, low grade dysplasia, prostatic hyperplasia, prostate cancer, melanoma, pancreatic cancer, brain cancer (such as a glioblastoma), hematological malignancy, hepatocellular carcinoma, cervical cancer, endometrial cancer, head and neck cancer, esophageal cancer, gastrointestinal stromal tumor (GIST), renal cell carcinoma (RCC) or gastric cancer. The colorectal cancer can be CRC Dukes B or Dukes C-D. The hematological malignancy can be B-Cell Chronic Lymphocytic Leukemia, B-Cell Lymphoma-DLBCL, B-Cell Lymphoma-DLBCL-germinal center-like, B-Cell Lymphoma-DLBCL-activated B-cell-like, and Burkitt's lymphoma.

The phenotype can be a premalignant condition, such as actinic keratosis, atrophic gastritis, leukoplakia, erythroplasia, Lymphomatoid Granulomatosis, preleukemia, fibrosis, cervical dysplasia, uterine cervical dysplasia, xeroderma pigmentosum, Barrett's Esophagus, colorectal polyp, or other abnormal tissue growth or lesion that is likely to develop into a malignant tumor. Transformative viral infections such as HIV and HPV also present phenotypes that can be assessed according to the invention.

A cancer characterized by the methods of the invention can comprise, without limitation, a carcinoma, a sarcoma, a lymphoma or leukemia, a germ cell tumor, a blastoma, or other cancers. Carcinomas include without limitation epithelial neoplasms, squamous cell neoplasms squamous cell carcinoma, basal cell neoplasms basal cell carcinoma, transitional cell papillomas and carcinomas, adenomas and adenocarcinomas (glands), adenoma, adenocarcinoma, linitis plastica insulinoma, glucagonoma, gastrinoma, vipoma, cholangiocarcinoma, hepatocellular carcinoma, adenoid cystic carcinoma, carcinoid tumor of appendix, prolactinoma, oncocytoma, hurthle cell adenoma, renal cell carcinoma, grawitz tumor, multiple endocrine adenomas, endometrioid adenoma, adnexal and skin appendage neoplasms, mucoepidermoid neoplasms, cystic, mucinous and serous neoplasms, cystadenoma, pseudomyxoma peritonei, ductal, lobular and medullary neoplasms, acinar cell neoplasms, complex epithelial neoplasms, warthin's tumor, thymoma, specialized gonadal neoplasms, sex cord stromal tumor, thecoma, granulosa cell tumor, arrhenoblastoma, sertoli leydig cell tumor, glomus tumors, paraganglioma, pheochromocytoma, glomus tumor, nevi and melanomas, melanocytic nevus, malignant melanoma, melanoma, nodular melanoma, dysplastic nevus, lentigo maligna melanoma, superficial spreading melanoma, and malignant acral lentiginous melanoma. Sarcoma includes without limitation Askin's tumor, botryodies, chondrosarcoma, Ewing's sarcoma, malignant hemangio endothelioma, malignant schwannoma, osteosarcoma, soft tissue sarcomas including: alveolar soft part sarcoma, angiosarcoma, cystosarcoma phyllodes, dermatofibrosarcoma, desmoid tumor, desmoplastic small round cell tumor, epithelioid sarcoma, extraskeletal chondrosarcoma, extraskeletal osteosarcoma, fibrosarcoma, hemangiopericytoma, hemangiosarcoma, kaposi's sarcoma, leiomyosarcoma, liposarcoma, lymphangiosarcoma, lymphosarcoma, malignant fibrous histiocytoma, neurofibrosarcoma, rhabdomyosarcoma, and synovialsarcoma. Lymphoma and leukemia include without limitation chronic lymphocytic leukemia/small lymphocytic lymphoma, B-cell prolymphocytic leukemia, lymphoplasmacytic lymphoma (such as waldenstrom macroglobulinemia), splenic marginal zone lymphoma, plasma cell myeloma, plasmacytoma, monoclonal immunoglobulin deposition diseases, heavy chain diseases, extranodal marginal zone B cell lymphoma, also called malt lymphoma, nodal marginal zone B cell lymphoma (nmzl), follicular lymphoma, mantle cell lymphoma, diffuse large B cell lymphoma, mediastinal (thymic) large B cell lymphoma, intravascular large B cell lymphoma, primary effusion lymphoma, burkitt lymphoma/leukemia, T cell prolymphocytic leukemia, T cell large granular lymphocytic leukemia, aggressive NK cell leukemia, adult T cell leukemia/lymphoma, extranodal NK/T cell lymphoma, nasal type, enteropathy-type T cell lymphoma, hepatosplenic T cell lymphoma, blastic NK cell lymphoma, mycosis fungoides/sezary syndrome, primary cutaneous CD30-positive T cell lymphoproliferative disorders, primary cutaneous anaplastic large cell lymphoma, lymphomatoid papulosis, angioimmunoblastic T cell lymphoma, peripheral T cell lymphoma, unspecified, anaplastic large cell lymphoma, classical hodgkin lymphomas (nodular sclerosis, mixed cellularity, lymphocyte-rich, lymphocyte depleted or not depleted), and nodular lymphocyte-predominant hodgkin lymphoma. Germ cell tumors include without limitation germinoma, dysgerminoma, seminoma, nongerminomatous germ cell tumor, embryonal carcinoma, endodermal sinus turmor, choriocarcinoma, teratoma, polyembryoma, and gonadoblastoma. Blastoma includes without limitation nephroblastoma, medulloblastoma, and retinoblastoma. Other cancers include without limitation labial carcinoma, larynx carcinoma, hypopharynx carcinoma, tongue carcinoma, salivary gland carcinoma, gastric carcinoma, adenocarcinoma, thyroid cancer (medullary and papillary thyroid carcinoma), renal carcinoma, kidney parenchyma carcinoma, cervix carcinoma, uterine corpus carcinoma, endometrium carcinoma, chorion carcinoma, testis carcinoma, urinary carcinoma, melanoma, brain tumors such as glioblastoma, astrocytoma, meningioma, medulloblastoma and peripheral neuroectodermal tumors, gall bladder carcinoma, bronchial carcinoma, multiple myeloma, basalioma, teratoma, retinoblastoma, choroidea melanoma, seminoma, rhabdomyosarcoma, craniopharyngeoma, osteosarcoma, chondrosarcoma, myosarcoma, liposarcoma, fibrosarcoma, Ewing sarcoma, and plasmocytoma.

In a further embodiment, the cancer under analysis may be a lung cancer including non-small cell lung cancer and small cell lung cancer (including small cell carcinoma (oat cell cancer), mixed small cell/large cell carcinoma, and combined small cell carcinoma), colon cancer, breast cancer, prostate cancer, liver cancer, pancreas cancer, brain cancer, kidney cancer, ovarian cancer, stomach cancer, skin cancer, bone cancer, gastric cancer, breast cancer, pancreatic cancer, glioma, glioblastoma, hepatocellular carcinoma, papillary renal carcinoma, head and neck squamous cell carcinoma, leukemia, lymphoma, myeloma, or a solid tumor.

In embodiments, the cancer comprises an acute lymphoblastic leukemia; acute myeloid leukemia; adrenocortical carcinoma; AIDS-related cancers; AIDS-related lymphoma; anal cancer; appendix cancer; astrocytomas; atypical teratoid/rhabdoid tumor; basal cell carcinoma; bladder cancer; brain stem glioma; brain tumor (including brain stem glioma, central nervous system atypical teratoid/rhabdoid tumor, central nervous system embryonal tumors, astrocytomas, craniopharyngioma, ependymoblastoma, ependymoma, medulloblastoma, medulloepithelioma, pineal parenchymal tumors of intermediate differentiation, supratentorial primitive neuroectodermal tumors and pineoblastoma); breast cancer; bronchial tumors; Burkitt lymphoma; cancer of unknown primary site; carcinoid tumor; carcinoma of unknown primary site; central nervous system atypical teratoid/rhabdoid tumor; central nervous system embryonal tumors; cervical cancer; childhood cancers; chordoma; chronic lymphocytic leukemia; chronic myelogenous leukemia; chronic myeloproliferative disorders; colon cancer; colorectal cancer; craniopharyngioma; cutaneous T-cell lymphoma; endocrine pancreas islet cell tumors; endometrial cancer; ependymoblastoma; ependymoma; esophageal cancer; esthesioneuroblastoma; Ewing sarcoma; extracranial germ cell tumor; extragonadal germ cell tumor; extrahepatic bile duct cancer; gallbladder cancer; gastric (stomach) cancer; gastrointestinal carcinoid tumor; gastrointestinal stromal cell tumor; gastrointestinal stromal tumor (GIST); gestational trophoblastic tumor; glioma; hairy cell leukemia; head and neck cancer; heart cancer; Hodgkin lymphoma; hypopharyngeal cancer; intraocular melanoma; islet cell tumors; Kaposi sarcoma; kidney cancer; Langerhans cell histiocytosis; laryngeal cancer; lip cancer; liver cancer; malignant fibrous histiocytoma bone cancer; medulloblastoma; medulloepithelioma; melanoma; Merkel cell carcinoma; Merkel cell skin carcinoma; mesothelioma; metastatic squamous neck cancer with occult primary; mouth cancer; multiple endocrine neoplasia syndromes; multiple myeloma; multiple myeloma/plasma cell neoplasm; mycosis fungoides; myelodysplastic syndromes; myeloproliferative neoplasms; nasal cavity cancer; nasopharyngeal cancer; neuroblastoma; Non-Hodgkin lymphoma; nonmelanoma skin cancer; non-small cell lung cancer; oral cancer; oral cavity cancer; oropharyngeal cancer; osteosarcoma; other brain and spinal cord tumors; ovarian cancer; ovarian epithelial cancer; ovarian germ cell tumor; ovarian low malignant potential tumor; pancreatic cancer; papillomatosis; paranasal sinus cancer; parathyroid cancer; pelvic cancer; penile cancer; pharyngeal cancer; pineal parenchymal tumors of intermediate differentiation; pineoblastoma; pituitary tumor; plasma cell neoplasm/multiple myeloma; pleuropulmonary blastoma; primary central nervous system (CNS) lymphoma; primary hepatocellular liver cancer; prostate cancer; rectal cancer; renal cancer; renal cell (kidney) cancer; renal cell cancer; respiratory tract cancer; retinoblastoma; rhabdomyosarcoma; salivary gland cancer; Sézary syndrome; small cell lung cancer; small intestine cancer; soft tissue sarcoma; squamous cell carcinoma; squamous neck cancer; stomach (gastric) cancer; supratentorial primitive neuroectodermal tumors; T-cell lymphoma; testicular cancer; throat cancer; thymic carcinoma; thymoma; thyroid cancer; transitional cell cancer; transitional cell cancer of the renal pelvis and ureter; trophoblastic tumor; ureter cancer; urethral cancer; uterine cancer; uterine sarcoma; vaginal cancer; vulvar cancer; Waldenström macroglobulinemia; or Wilm's tumor. The methods of the invention can be used to characterize these and other cancers. Thus, characterizing a phenotype can be providing a diagnosis, prognosis or theranosis of one of the cancers disclosed herein.

In some embodiments, the cancer comprises an acute myeloid leukemia (AML), breast carcinoma, cholangiocarcinoma, colorectal adenocarcinoma, extrahepatic bile duct adenocarcinoma, female genital tract malignancy, gastric adenocarcinoma, gastroesophageal adenocarcinoma, gastrointestinal stromal tumors (GIST), glioblastoma, head and neck squamous carcinoma, leukemia, liver hepatocellular carcinoma, low grade glioma, lung bronchioloalveolar carcinoma (BAC), lung non-small cell lung cancer (NSCLC), lung small cell cancer (SCLC), lymphoma, male genital tract malignancy, malignant solitary fibrous tumor of the pleura (MSFT), melanoma, multiple myeloma, neuroendocrine tumor, nodal diffuse large B-cell lymphoma, non epithelial ovarian cancer (non-EOC), ovarian surface epithelial carcinoma, pancreatic adenocarcinoma, pituitary carcinomas, oligodendroglioma, prostatic adenocarcinoma, retroperitoneal or peritoneal carcinoma, retroperitoneal or peritoneal sarcoma, small intestinal malignancy, soft tissue tumor, thymic carcinoma, thyroid carcinoma, or uveal melanoma. The methods of the invention can be used to characterize these and other cancers. Thus, characterizing a phenotype can be providing a diagnosis, prognosis or theranosis of one of the cancers disclosed herein.

The phenotype can also be an inflammatory disease, immune disease, or autoimmune disease. For example, the disease may be inflammatory bowel disease (IBD), Crohn's disease (CD), ulcerative colitis (UC), pelvic inflammation, vasculitis, psoriasis, diabetes, autoimmune hepatitis, Multiple Sclerosis, Myasthenia Gravis, Type I diabetes, Rheumatoid Arthritis, Psoriasis, Systemic Lupus Erythematosis (SLE), Hashimoto's Thyroiditis, Grave's disease, Ankylosing Spondylitis Sjogrens Disease, CREST syndrome, Scleroderma, Rheumatic Disease, organ rejection, Primary Sclerosing Cholangitis, or sepsis.

The phenotype can also comprise a cardiovascular disease, such as atherosclerosis, congestive heart failure, vulnerable plaque, stroke, or ischemia. The cardiovascular disease or condition can be high blood pressure, stenosis, vessel occlusion or a thrombotic event.

The phenotype can also comprise a neurological disease, such as Multiple Sclerosis (MS), Parkinson's Disease (PD), Alzheimer's Disease (AD), schizophrenia, bipolar disorder, depression, autism, Prion Disease, Pick's disease, dementia, Huntington disease (HD), Down's syndrome, cerebrovascular disease, Rasmussen's encephalitis, viral meningitis, neurospsychiatric systemic lupus erythematosus (NPSLE), amyotrophic lateral sclerosis, Creutzfeldt-Jacob disease, Gerstmann-Straussler-Scheinker disease, transmissible spongiform encephalopathy, ischemic reperfusion damage (e.g. stroke), brain trauma, microbial infection, or chronic fatigue syndrome. The phenotype may also be a condition such as fibromyalgia, chronic neuropathic pain, or peripheral neuropathic pain.

The phenotype may also comprise an infectious disease, such as a bacterial, viral or yeast infection. For example, the disease or condition may be Whipple's Disease, Prion Disease, cirrhosis, methicillin-resistant staphylococcus aureus, HIV, hepatitis, syphilis, meningitis, malaria, tuberculosis, or influenza. Viral proteins, such as HIV or HCV-like particles can be assessed in a vesicle, to characterize a viral condition.

The phenotype can also comprise a perinatal or pregnancy related condition (e.g. preeclampsia or preterm birth), metabolic disease or condition, such as a metabolic disease or condition associated with iron metabolism. For example, hepcidin can be assayed in a vesicle to characterize an iron deficiency. The metabolic disease or condition can also be diabetes, inflammation, or a perinatal condition.

The compositions and methods of the invention can be used to characterize these and other diseases and disorders that can be assessed via biomarkers. Thus, characterizing a phenotype can be providing a diagnosis, prognosis or theranosis of one of the diseases and disorders disclosed herein.

Subject

One or more phenotypes of a subject can be determined by analyzing one or more vesicles, such as vesicles, in a biological sample obtained from the subject. A subject or patient can include, but is not limited to, mammals such as bovine, avian, canine, equine, feline, ovine, porcine, or primate animals (including humans and non-human primates). A subject can also include a mammal of importance due to being endangered, such as a Siberian tiger; or economic importance, such as an animal raised on a farm for consumption by humans, or an animal of social importance to humans, such as an animal kept as a pet or in a zoo. Examples of such animals include, but are not limited to, carnivores such as cats and dogs; swine including pigs, hogs and wild boars; ruminants or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, camels or horses. Also included are birds that are endangered or kept in zoos, as well as fowl and more particularly domesticated fowl, i.e. poultry, such as turkeys and chickens, ducks, geese, guinea fowl. Also included are domesticated swine and horses (including race horses). In addition, any animal species connected to commercial activities are also included such as those animals connected to agriculture and aquaculture and other activities in which disease monitoring, diagnosis, and therapy selection are routine practice in husbandry for economic productivity and/or safety of the food chain.

The subject can have a pre-existing disease or condition, such as cancer. Alternatively, the subject may not have any known pre-existing condition. The subject may also be non-responsive to an existing or past treatment, such as a treatment for cancer.

Subject

One or more phenotypes of a subject can be determined by analyzing one or more vesicles, such as vesicles, in a biological sample obtained from the subject. A subject or patient can include, but is not limited to, mammals such as bovine, avian, canine, equine, feline, ovine, porcine, or primate animals (including humans and non-human primates). A subject can also include a mammal of importance due to being endangered, such as a Siberian tiger; or economic importance, such as an animal raised on a farm for consumption by humans, or an animal of social importance to humans, such as an animal kept as a pet or in a zoo. Examples of such animals include, but are not limited to, carnivores such as cats and dogs; swine including pigs, hogs and wild boars; ruminants or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, camels or horses. Also included are birds that are endangered or kept in zoos, as well as fowl and more particularly domesticated fowl, i.e. poultry, such as turkeys and chickens, ducks, geese, guinea fowl. Also included are domesticated swine and horses (including race horses). In addition, any animal species connected to commercial activities are also included such as those animals connected to agriculture and aquaculture and other activities in which disease monitoring, diagnosis, and therapy selection are routine practice in husbandry for economic productivity and/or safety of the food chain.

The subject can have a pre-existing disease or condition, such as cancer. Alternatively, the subject may not have any known pre-existing condition. The subject may also be non-responsive to an existing or past treatment, such as a treatment for cancer.

Samples

A sample used and/or assessed via the compositions and methods of the invention includes any relevant biological sample that can be used for biomarker assessment, including without limitation sections of tissues such as biopsy or tissue removed during surgical or other procedures, bodily fluids, autopsy samples, frozen sections taken for histological purposes, and cell cultures. Such samples include blood and blood fractions or products (e.g., serum, buffy coat, plasma, platelets, red blood cells, and the like), sputum, malignant effusion, cheek cells tissue, cultured cells (e.g., primary cultures, explants, and transformed cells), stool, urine, other biological or bodily fluids (e.g., prostatic fluid, gastric fluid, intestinal fluid, renal fluid, lung fluid, cerebrospinal fluid, and the like), etc. The sample can comprise biological material that is a fresh frozen & formalin fixed paraffin embedded (FFPE) block, formalin-fixed paraffin embedded, or is within an RNA preservative+formalin fixative. More than one sample of more than one type can be used for each patient.

The sample used in the methods described herein can be a formalin fixed paraffin embedded (FFPE) sample. The FFPE sample can be one or more of fixed tissue, unstained slides, bone marrow core or clot, core needle biopsy, malignant fluids and fine needle aspirate (FNA). In an embodiment, the fixed tissue comprises a tumor containing formalin fixed paraffin embedded (FFPE) block from a surgery or biopsy. In another embodiment, the unstained slides comprise unstained, charged, unbaked slides from a paraffin block. In another embodiment, bone marrow core or clot comprises a decalcified core. A formalin fixed core and/or clot can be paraffin-embedded. In still another embodiment, the core needle biopsy comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more, e.g., 3-4, paraffin embedded biopsy samples. An 18 gauge needle biopsy can be used. The malignant fluid can comprise a sufficient volume of fresh pleural/ascitic fluid to produce a 5×5×2 mm cell pellet. The fluid can be formalin fixed in a paraffin block. In an embodiment, the core needle biopsy comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more, e.g., 4-6, paraffin embedded aspirates.

A sample may be processed according to techniques understood by those in the art. A sample can be without limitation fresh, frozen or fixed cells or tissue. In some embodiments, a sample comprises formalin-fixed paraffin-embedded (FFPE) tissue, fresh tissue or fresh frozen (FF) tissue. A sample can comprise cultured cells, including primary or immortalized cell lines derived from a subject sample. A sample can also refer to an extract from a sample from a subject. For example, a sample can comprise DNA, RNA or protein extracted from a tissue or a bodily fluid. Many techniques and commercial kits are available for such purposes. The fresh sample from the individual can be treated with an agent to preserve RNA prior to further processing, e.g., cell lysis and extraction. Samples can include frozen samples collected for other purposes. Samples can be associated with relevant information such as age, gender, and clinical symptoms present in the subject; source of the sample; and methods of collection and storage of the sample. A sample is typically obtained from a subject.

A biopsy comprises the process of removing a tissue sample for diagnostic or prognostic evaluation, and to the tissue specimen itself. Any biopsy technique known in the art can be applied to the molecular profiling methods of the present invention. The biopsy technique applied can depend on the tissue type to be evaluated (e.g., colon, prostate, kidney, bladder, lymph node, liver, bone marrow, blood cell, lung, breast, etc.), the size and type of the tumor (e.g., solid or suspended, blood or ascites), among other factors. Representative biopsy techniques include, but are not limited to, excisional biopsy, incisional biopsy, needle biopsy, surgical biopsy, and bone marrow biopsy. An “excisional biopsy” refers to the removal of an entire tumor mass with a small margin of normal tissue surrounding it. An “incisional biopsy” refers to the removal of a wedge of tissue that includes a cross-sectional diameter of the tumor. Molecular profiling can use a “core-needle biopsy” of the tumor mass, or a “fine-needle aspiration biopsy” which generally obtains a suspension of cells from within the tumor mass. Biopsy techniques are discussed, for example, in Harrison's Principles of Internal Medicine, Kasper, et al., eds., 16th ed., 2005, Chapter 70, and throughout Part V.

Standard molecular biology techniques known in the art and not specifically described are generally followed as in Sambrook et al., Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, New York (1989), and as in Ausubel et al., Current Protocols in Molecular Biology, John Wiley and Sons, Baltimore, Md. (1989) and as in Perbal, A Practical Guide to Molecular Cloning, John Wiley & Sons, New York (1988), and as in Watson et al., Recombinant DNA, Scientific American Books, New York and in Birren et al (eds) Genome Analysis: A Laboratory Manual Series, Vols. 1-4 Cold Spring Harbor Laboratory Press, New York (1998) and methodology as set forth in U.S. Pat. Nos. 4,666,828; 4,683,202; 4,801,531; 5,192,659 and 5,272,057 and incorporated herein by reference. Polymerase chain reaction (PCR) can be carried out generally as in PCR Protocols: A Guide to Methods and Applications, Academic Press, San Diego, Calif. (1990).

The biological sample assessed using the compositions and methods of the invention can be any useful bodily or biological fluid, including but not limited to peripheral blood, sera, plasma, ascites, urine, cerebrospinal fluid (CSF), sputum, saliva, bone marrow, synovial fluid, aqueous humor, amniotic fluid, cerumen, breast milk, broncheoalveolar lavage fluid, semen (including prostatic fluid), Cowper's fluid or pre-ejaculatory fluid, female ejaculate, sweat, fecal matter, hair, tears, cyst fluid, pleural and peritoneal fluid, pericardial fluid, lymph, chyme, chyle, bile, interstitial fluid, menses, pus, sebum, vomit, vaginal secretions, mucosal secretion, stool water, pancreatic juice, lavage fluids from sinus cavities, bronchopulmonary aspirates, other lavage fluids, cells, cell culture, or a cell culture supernatant. A biological sample may also include the blastocyl cavity, umbilical cord blood, or maternal circulation which may be of fetal or maternal origin. The biological sample may also be a cell culture, tissue sample or biopsy from which vesicles and other circulating biomarkers may be obtained. For example, cells of interest can be cultured and vesicles isolated from the culture. In various embodiments, biomarkers or more particularly biosignatures disclosed herein can be assessed directly from such biological samples (e.g., identification of presence or levels of nucleic acid or polypeptide biomarkers or functional fragments thereof) using various methods, such as extraction of nucleic acid molecules from blood, plasma, serum or any of the foregoing biological samples, use of protein or antibody arrays to identify polypeptide (or functional fragment) biomarker(s), as well as other array, sequencing, PCR and proteomic techniques known in the art for identification and assessment of nucleic acid and polypeptide molecules. In addition, one or more components present in such samples can be first isolated or enriched and further processed to assess the presence or levels of selected biomarkers, to assess a given biosignature (e.g., isolated microvesicles prior to profiling for protein and/or nucleic acid biomarkers).

The methods of the invention can be used to characterize a phenotype using a blood sample or blood derivative. Blood derivatives include plasma and serum. Blood plasma is the liquid component of whole blood, and makes up approximately 55% of the total blood volume. It is composed primarily of water with small amounts of minerals, salts, ions, nutrients, and proteins in solution. In whole blood, red blood cells, leukocytes, and platelets are suspended within the plasma. Blood serum refers to blood plasma without fibrinogen or other clotting factors (i.e., whole blood minus both the cells and the clotting factors).

The biological sample may be obtained through a third party, such as a party not performing the analysis of the biomarkers, whether direct assessment of a biological sample or by profiling one or more vesicles obtained from the biological sample. For example, the sample may be obtained through a clinician, physician, or other health care manager of a subject from which the sample is derived. Alternatively, the biological sample may obtained by the same party analyzing the vesicle. In addition, biological samples be assayed, are archived (e.g., frozen) or otherwise stored in under preservative conditions.

Furthermore, a biological sample can comprise a vesicle or cell membrane fragment that is derived from a cell of origin and available extracellularly in a subject's biological fluid or extracellular milieu.

Methods of the invention can include assessing one or more vesicles, including assessing vesicle populations. A vesicle, as used herein, is a membrane vesicle that is shed from cells. Vesicles or membrane vesicles include without limitation: circulating microvesicles (cMVs), microvesicle, exosome, nanovesicle, dexosome, bleb, blebby, prostasome, microparticle, intralumenal vesicle, membrane fragment, intralumenal endosomal vesicle, endosomal-like vesicle, exocytosis vehicle, endosome vesicle, endosomal vesicle, apoptotic body, multivesicular body, secretory vesicle, phospholipid vesicle, liposomal vesicle, argosome, texasome, secresome, tolerosome, melanosome, oncosome, or exocytosed vehicle. Furthermore, although vesicles may be produced by different cellular processes, the methods of the invention are not limited to or reliant on any one mechanism, insofar as such vesicles are present in a biological sample and are capable of being characterized by the methods disclosed herein. Unless otherwise specified, methods that make use of a species of vesicle can be applied to other types of vesicles. Vesicles comprise spherical structures with a lipid bilayer similar to cell membranes which surrounds an inner compartment which can contain soluble components, sometimes referred to as the payload. In some embodiments, the methods of the invention make use of exosomes, which are small secreted vesicles of about 40-100 nm in diameter. For a review of membrane vesicles, including types and characterizations, see Thery et al., Nat Rev Immunol. 2009 August; 9(8):581-93. Some properties of different types of vesicles include those in Table 1:

TABLE 1 Vesicle Properties Membrane Exosome- Apoptotic Feature Exosomes Microvesicles Ectosomes particles like vesicles vesicles Size 50-100 nm 100-1,000 nm 50-200 nm 50-80 nm 20-50 nm 50-500 nm Density in 1.13-1.19 g/ml 1.04-1.07 g/ml 1.1 g/ml 1.16-1.28 g/ml sucrose EM appearance Cup shape Irregular Bilamellar Round Irregular Heterogeneous shape, electron round structures shape dense Sedimentation 100,000 g 10,000 g 160,000- 100,000- 175,000 g 1,200 g, 200,000 g 200,000 g 10,000 g, 100,000 g Lipid Enriched in Expose PPS Enriched in No lipid rafts composition cholesterol, cholesterol and sphingomyelin diacylglycerol; and ceramide; expose PPS contains lipid rafts; expose PPS Major protein Tetraspanins Integrins, CR1 and CD133; no TNFRI Histones markers (e.g., CD63, selectins and proteolytic CD63 CD9), Alix, CD40 ligand enzymes; no TSG101 CD63 Intracellular Internal Plasma Plasma Plasma origin compartments membrane membrane membrane (endosomes) Abbreviations: phosphatidylserine (PPS); electron microscopy (EM)

Vesicles include shed membrane bound particles, or “microparticles,” that are derived from either the plasma membrane or an internal membrane. Vesicles can be released into the extracellular environment from cells. Cells releasing vesicles include without limitation cells that originate from, or are derived from, the ectoderm, endoderm, or mesoderm. The cells may have undergone genetic, environmental, and/or any other variations or alterations. For example, the cell can be tumor cells. A vesicle can reflect any changes in the source cell, and thereby reflect changes in the originating cells, e.g., cells having various genetic mutations. In one mechanism, a vesicle is generated intracellularly when a segment of the cell membrane spontaneously invaginates and is ultimately exocytosed (see for example, Keller et al., Immunol. Lett. 107 (2): 102-8 (2006)). Vesicles also include cell-derived structures bounded by a lipid bilayer membrane arising from both herniated evagination (blebbing) separation and sealing of portions of the plasma membrane or from the export of any intracellular membrane-bounded vesicular structure containing various membrane-associated proteins of tumor origin, including surface-bound molecules derived from the host circulation that bind selectively to the tumor-derived proteins together with molecules contained in the vesicle lumen, including but not limited to tumor-derived microRNAs or intracellular proteins. Blebs and blebbing are further described in Charras et al., Nature Reviews Molecular and Cell Biology, Vol. 9, No. 11, p. 730-736 (2008). A vesicle shed into circulation or bodily fluids from tumor cells may be referred to as a “circulating tumor-derived vesicle.” When such vesicle is an exosome, it may be referred to as a circulating-tumor derived exosome (CTE). In some instances, a vesicle can be derived from a specific cell of origin. CTE, as with a cell-of-origin specific vesicle, typically have one or more unique biomarkers that permit isolation of the CTE or cell-of-origin specific vesicle, e.g., from a bodily fluid and sometimes in a specific manner. For example, a cell or tissue specific markers are used to identify the cell of origin. Examples of such cell or tissue specific markers are disclosed herein and can further be accessed in the Tissue-specific Gene Expression and Regulation (TiGER) Database, available at bioinfo.wilmer.jhu.edu/tiger/; Liu et al. (2008) TiGER: a database for tissue-specific gene expression and regulation. BMC Bioinformatics. 9:271; TissueDistributionDBs, available at genome dkfz-heidelberg.de/menu/tissue_db/index.html.

A vesicle can have a diameter of greater than about 10 nm, 20 nm, or 30 nm. A vesicle can have a diameter of greater than 40 nm, 50 nm, 100 nm, 200 nm, 500 nm, 1000 nm, 1500 nm, 2000 nm or greater than 10,000 nm. A vesicle can have a diameter of about 20-2000 nm, about 20-1500 nm, about 30-1000 nm, about 30-800 nm, about 30-200 nm, or about 30-100 nm. In some embodiments, the vesicle has a diameter of less than 10,000 nm, 2000 nm, 1500 nm, 1000 nm, 800 nm, 500 nm, 200 nm, 100 nm, 50 nm, 40 nm, 30 nm, 20 nm or less than 10 nm. As used herein the term “about” in reference to a numerical value means that variations of 10% above or below the numerical value are within the range ascribed to the specified value. Typical sizes for various types of vesicles are shown in Table 1. Vesicles can be assessed to measure the diameter of a single vesicle or any number of vesicles. For example, the range of diameters of a vesicle population or an average diameter of a vesicle population can be determined. Vesicle diameter can be assessed using methods known in the art, e.g., imaging technologies such as electron microscopy. In an embodiment, a diameter of one or more vesicles is determined using optical particle detection. See, e.g., U.S. Pat. No. 7,751,053, entitled “Optical Detection and Analysis of Particles” and issued Jul. 6, 2010; and U.S. Pat. No. 7,399,600, entitled “Optical Detection and Analysis of Particles” and issued Jul. 15, 2010.

In some embodiments, vesicles are directly assayed from a biological sample without prior isolation, purification, or concentration from the biological sample. For example, the amount of vesicles in the sample can by itself provide a biosignature that provides a diagnostic, prognostic or theranostic determination. Alternatively, the vesicle in the sample may be isolated, captured, purified, or concentrated from a sample prior to analysis. As noted, isolation, capture or purification as used herein comprises partial isolation, partial capture or partial purification apart from other components in the sample. Vesicle isolation can be performed using various techniques as described herein, e.g., chromatography, filtration, centrifugation, flow cytometry, affinity capture (e.g., to a planar surface or bead), and/or using microfluidics.

Vesicles such as exosomes can be assessed to provide a phenotypic characterization by comparing vesicle characteristics to a reference. In some embodiments, surface antigens on a vesicle are assessed. The surface antigens can provide an indication of the anatomical origin and/or cellular of the vesicles and other phenotypic information, e.g., tumor status. For example, wherein vesicles found in a patient sample, e.g., a bodily fluid such as blood, serum or plasma, are assessed for surface antigens indicative of colorectal origin and the presence of cancer. The surface antigens may comprise any informative biological entity that can be detected on the vesicle membrane surface, including without limitation surface proteins, lipids, carbohydrates, and other membrane components. For example, positive detection of colon derived vesicles expressing tumor antigens can indicate that the patient has colorectal cancer. As such, methods of the invention can be used to characterize any disease or condition associated with an anatomical or cellular origin, by assessing, for example, disease-specific and cell-specific biomarkers of one or more vesicles obtained from a subject.

In another embodiment, one or more vesicle payloads are assessed to provide a phenotypic characterization. The payload with a vesicle comprises any informative biological entity that can be detected as encapsulated within the vesicle, including without limitation proteins and nucleic acids, e.g., genomic or cDNA, mRNA, or functional fragments thereof, as well as microRNAs (miRs). In addition, methods of the invention are directed to detecting vesicle surface antigens (in addition or exclusive to vesicle payload) to provide a phenotypic characterization. For example, vesicles can be characterized by using binding agents (e.g., antibodies or aptamers) that are specific to vesicle surface antigens, and the bound vesicles can be further assessed to identify one or more payload components disclosed therein. As described herein, the levels of vesicles with surface antigens of interest or with payload of interest can be compared to a reference to characterize a phenotype. For example, overexpression in a sample of cancer-related surface antigens or vesicle payload, e.g., a tumor associated mRNA or microRNA, as compared to a reference, can indicate the presence of cancer in the sample. The biomarkers assessed can be present or absent, increased or reduced based on the selection of the desired target sample and comparison of the target sample to the desired reference sample. Non-limiting examples of target samples include: disease; treated/not-treated; different time points, such as a in a longitudinal study; and non-limiting examples of reference sample: non-disease; normal; different time points; and sensitive or resistant to candidate treatment(s).

Biomarkers

As described herein, the methods and compositions of the invention can be used in assays to detect the presence or level of one or more biomarker of interest. The biomarker can be any useful biomarker disclosed herein or known to those of skill in the art. In an embodiment, the biomarker comprises a protein or polypeptide. As used herein, “protein,” “polypeptide” and “peptide” are used interchangeably unless stated otherwise. The biomarker can be a nucleic acid, including DNA, RNA, and various subspecies of any thereof as disclosed herein or known in the art. The biomarker can comprise a lipid. The biomarker can comprise a carbohydrate. The biomarker can also be a complex, e.g., a complex comprising protein, nucleic acids, lipids and/or carbohydrates. In some embodiments, the biomarker comprises a microvesicle. A biosignature comprising more than one biomarker can comprise one type of biomarker or multiple types of biomarkers. As a non-limiting example, a biosignature can comprise multiple proteins, multiple nucleic acids, multiple lipids, multiple carbohydrates, multiple biomarker complexes, multiple microvesicles, or a combination of any thereof. For example, the biosignature may comprises one or more microvesicle, one or more protein, and one or more microRNA, wherein the one or more protein and/or one or more microRNA is optionally in association with the microvesicle as a surface antigen and/or payload, as appropriate.

In some embodiments, vesicles are detected using vesicle surface antigens. A commonly expressed vesicle surface antigen can be referred to as a “housekeeping protein,” or general vesicle biomarker. The biomarker can be CD63, CD9, CD81, CD82, CD37, CD53, Rab-5b, Annexin V or MFG-E8. Tetraspanins, a family of membrane proteins with four transmembrane domains, can be used as general vesicle biomarkers. The tetraspanins include CD151, CD53, CD37, CD82, CD81, CD9 and CD63. There have been over 30 tetraspanins identified in mammals, including the TSPAN1 (TSP-1), TSPAN2 (TSP-2), TSPAN3 (TSP-3), TSPAN4 (TSP-4, NAG-2), TSPAN5 (TSP-5), TSPAN6 (TSP-6), TSPAN7 (CD231, TALLA-1, A15), TSPAN8 (CO-029), TSPAN9 (NET-5), TSPAN10 (Oculospanin), TSPAN11 (CD151-like), TSPAN12 (NET-2), TSPAN13 (NET-6), TSPAN14, TSPAN15 (NET-7), TSPAN16 (TM4-B), TSPAN17, TSPAN18, TSPAN19, TSPAN20 (UP1b, UPK1B), TSPAN21 (UPla, UPK1A), TSPAN22 (RDS, PRPH2), TSPAN23 (ROM1), TSPAN24 (CD151), TSPAN25 (CD53), TSPAN26 (CD37), TSPAN28 (CD82), TSPAN28 (CD81), TSPAN29 (CD9), TSPAN30 (CD63), TSPAN31 (SAS), TSPAN32 (TSSC6), TSPAN33, and TSPAN34. Other commonly observed vesicle markers include those listed in Table 2. One or more of these proteins can be useful biomarkers for the characterizing a phenotype using the subject methods and compositions.

TABLE 2 Proteins Observed in Vesicles from Multiple Cell Types Class Protein Antigen MHC class I, MHC class II, Integrins, Alpha Presentation 4 beta 1, Alpha M beta 2, Beta 2 Immunoglobulin family ICAM1/CD54, P-selection Cell-surface peptidases Dipeptidylpeptidase IV/CD26, Aminopeptidase n/CD13 Tetraspanins CD151, CD53, CD37, CD82, CD81, CD9 and CD63 Heat-shock proteins Hsp70, Hsp84/90 Cytoskeletal proteins Actin, Actin-binding proteins, Tubulin Membrane transport Annexin I, Annexin II, Annexin IV, and fusion Annexin V, Annexin VI, RAB7/RAP1B/RADGDI Signal transduction Gi2alpha/14-3-3, CBL/LCK Abundant membrane CD63, GAPDH, CD9, CD81, ANXA2, ENO1, proteins SDCBP, MSN, MFGE8, EZR, GK, ANXA1, LAMP2, DPP4, TSG101, HSPA1A, GDI2, CLTC, LAMP1, Cd86, ANPEP, TFRC, SLC3A2, RDX, RAP1B, RAB5C, RAB5B, MYH9, ICAM1, FN1, RAB11B, PIGR, LGALS3, ITGB1, EHD1, CLIC1, ATP1A1, ARF1, RAP1A, P4HB, MUC1, KRT10, HLA-A, FLOT1, CD59, C1orf58, BASP1, TACSTD1, STOM Other Cadherins: CDH1, CDH2, CDH12, CDH3, Transmembrane Deomoglein, DSG1, DSG2, DSG3, Proteins DSG4, Desmocollin, DSC1, DSG2, DSG3, Protocadherins, PCDH1, PCDH10, PCDH11x, PCDH11y, PCDH12, FAT, FAT2, FAT4, PCDH15, PCDH17, PCDH18, PCDH19; PCDH20; PCDH7, PCDH8, PCDH9, PCDHAL PCDHA10, PCDHA11, PCDHA12, PCDHA13, PCDHA2, PCDHA3, PCDHA4, PCDHA5, PCDHA6, PCDHA7, PCDHA8, PCDHA9, PCDHAC1, PCDHAC2, PCDHB1, PCDHB10, PCDHB11, PCDHB12, PCDHB13, PCDHB14, PCDHB15, PCDHB16, PCDHB17, PCDHB18, PCDHB2, PCDHB3, PCDHB4, PCDHB5, PCDHB6, PCDHB7, PCDHB8, PCDHB9, PCDHGA1, PCDHGA10, PCDHGA11, PCDHGA12, PCDHGA2; PCDHGA3, PCDHGA4, PCDHGA5, PCDHGA6, PCDHGA7, PCDHGA8, PCDHGA9, PCDHGB1, PCDHGB2, PCDHGB3, PCDHGB4, PCDHGB5, PCDHGB6, PCDHGB7, PCDHGC3, PCDHGC4, PCDHGC5, CDH9 (cadherin 9, type 2 (T1-cadherin)), CDH10 (cadherin 10, type 2 (T2-cadherin)), CDH5 (VE- cadherin (vascular endothelial)), CDH6 (K-cadherin (kidney)), CDH7 (cadherin 7, type 2), CDH8 (cadherin 8, type 2), CDH11 (OB-cadherin (osteoblast)), CDH13 (T-cadherin-H-cadherin (heart)), CDH15 (M-cadherin (myotubule)), CDH16 (KSP-cadherin), CDH17 (LI cadherin (liver-intestine)), CDH18 (cadherin 18, type 2), CDH19 (cadherin 19, type 2), CDH20 (cadherin 20, type 2), CDH23 (cadherin 23, (neurosensory epithelium)), CDH10, CDH11, CDH13, CDH15, CDH16, CDH17, CDH18, CDH19, CDH20, CDH22, CDH23, CDH24, CDH26, CDH28, CDH4, CDH5, CDH6, CDH7, CDH8, CDH9, CELSR1, CELSR2, CELSR3, CLSTN1, CLSTN2, CLSTN3, DCHS1, DCHS2, LOC389118, PCLKC, RESDA1, RET

Any of the types of biomarkers described herein can be assessed using the subject methods and compositions. Exemplary biomarkers include without limitation those in Table 3. The markers can be detected as protein or as mRNA, which can be circulating freely or in a complex with other biological molecules. As appropriate, the markers in Table 3 can also be used for capture and/or detection of vesicles for characterizing phenotypes as disclosed herein. In some cases, multiple capture and/or detectors are used to enhance the characterization. The markers can be detected as vesicle surface antigens and/or vesicle payload. The “Illustrative Class” indicates indications for which the markers are known markers. Those of skill will appreciate that the markers can also be used in alternate settings in certain instances. For example, a marker which can be used to characterize one type disease may also be used to characterize another disease as appropriate. Consider a non-limiting example of a tumor marker which can be used as a biomarker for tumors from various lineages. The biomarker references in Table 3 are those commonly used in the art. Gene aliases and descriptions can be found using a variety of online databases, including GeneCards® (www.genecards.org), HUGO Gene Nomenclature (www.genenames.org), Entrez Gene (www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene), UniProtKB/Swiss-Prot (www.uniprot.org), UniProtKB/TrEMBL (www.uniprot.org), OMIM (www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM), GeneLoc (genecards.weizmann.ac.il/geneloc/), and Ensembl (www.ensembl.org). Generally, gene symbols and names below correspond to those approved by HUGO, and protein names are those recommended by UniProtKB/Swiss-Prot. Common alternatives are provided as well. In some cases, biomarkers are referred to by Ensembl reference numbers, which are of the form “ENSG” followed by a number, e.g., ENSG00000005893 which corresponds to LAMP2. In Table 3, solely for sake of brevity, “E.” is sometimes used to represent “ENSG00000”. For example, “E.005893 represents “ENSG00000005893.” Where a protein name indicates a precursor, the mature protein is also implied. Throughout the application, gene and protein symbols may be used interchangeably and the meaning can be derived from context as necessary.

TABLE 3 Illustrative Biomarkers Illustrative Class Biomarkers Drug associated ABCC1, ABCG2, ACE2, ADA, ADH1C, ADH4, targets and AGT, AR, AREG, ASNS, BCL2, BCRP, prognostic BDCA1, beta III tubulin, BIRCS, B-RAF, BRCA1, markers BRCA2, CA2, caveolin, CD20, CD25, CD33, CD52, CDA, CDKN2A, CDKN1A, CDKN1B, CDK2, CDW52, CES2, CK 14, CK 17, CK 5/6, c-KIT, c-Met, c-Myc, COX-2, Cyclin D1, DCK, DHFR, DNMT1, DNMT3A, DNMT3B, E-Cadherin, ECGF1, EGFR, EML4-ALK fusion, EPHA2, Epiregulin, ER, ERBR2, ERCC1, ERCC3, EREG, ESR1, FLT1, folate receptor, FOLR1, FOLR2, FSHB, FSHPRH1, FSHR, FYN, GART, GNA11, GNAQ, GNRH1, GNRHR1, GSTP1, HCK, HDAC1, KENT-1, Her2/Neu, HGF, HIF1A, HIG1, HSP90, HSP90AA1, HSPCA, IGF-1R, IGFRBP, IGFRBP3, IGFRBP4, IGFRBP5, IL13RA1, IL2RA, KDR, Ki67, KIT, K-RAS, LCK, LTB, Lymphotoxin Beta Receptor, LYN, MET, MGMT, MLH1, MMR, MRP1, MS4A1, MSH2, MSH5, Myc, NFKB1, NFKB2, NFKBIA, NRAS, ODC1, OGFR, p16, p21, p27, p53, p95, PARP-1, PDGFC, PDGFR, PDGFRA, PDGFRB, PGP, PGR, PI3K, POLA, POLA1, PPARG, PPARGC1, PR, PTEN, PTGS2, PTPN12, RAF1, RARA, ROS1, RRM1, RRM2, RRM2B, RXRB, RXRG, SIK2, SPARC, SRC, SSTR1, SSTR2, SSTR3, SSTR4, SSTR5, Survivin, TK1, TLE3, TNF, TOP1, TOP2A, TOP2B, TS, TUBB3, TXN, TXNRDL TYMS, VDR, VEGF, VEGFA, VEGFC, VHL, YES1, ZAP70 Drug associated ABL1, STK11, FGFR2, ERBB4, SMARCB1, targets and CDKN2A, CTNNB1, FGFR1, FLT3, prognostic NOTCH1, NPM1, SRC, SMAD4, FBXW7, PTEN, markers TP53, AKT1, ALK, APC, CDH1, C-Met, HRAS, IDH1, JAK2, MPL, PDGFRA, SMO, VHL, ATM, CSF1R, FGFR3, GNAS, ERBB2, HNF1A, JAK3, KDR, MLH1, PTPN11, RB1, RET, c-Kit, EGFR, PIK3CA, NRAS, GNA11, GNAQ, KRAS, BRAF Drug associated ALK, AR, BRAF, cKIT, cMET, EGFR, ER, ERCC1, targets and GNA11, HER2, IDH1, KRAS, MGMT, prognostic markers MGMT promoter methylation, NRAS, PDGFRA, Pgp, PIK3CA, PR, PTEN, ROS1, RRM1, SPARC, TLE3, TOP2A, TOPO1, TS, TUBB3, VHL Drug associated AR, cMET, EGFR, ER, HER2, MGMT, Pgp, PR, targets and PTEN, RRM1, SPARC, TLE3, TOPO1, prognostic markers TOP2A, TS, TUBB3, ALK, cMET, HER2, ROS1, TOP2A, BRAF, IDH2, MGMT Methylation, ABL1, AKT1, ALK, APC, ATM, BRAF, CDH1, CSF1R, CTNNB1, EGFR, ERBB2 (HER2), ERBB4, FBXW7, FGFR1, FGFR2, FLT3, GNA11, GNAQ, GNAS, HNF1A, HRAS, IDH1, JAK2, JAK3, KDR (VEGFR2), KIT, KRAS, MET, MLH1, MPL, NOTCH1, NPM1, NRAS, PDGFRA, PIK3CA, PTEN, PTPN11, RB1, RET, SMAD4, SMARCB1, SMO, STK11, TP53, VHL 5-aminosalicyclic μ-protocadherin, KLF4, CEBPα acid (5-ASA) efficacy Cancer treatment AR, AREG (Amphiregulin), BRAF, BRCA1, cKIT, associated markers cMET, EGFR, EGFR w/T790M, EML4- ALK, ER, ERBB3, ERBB4, ERCC1, EREG, GNA11, GNAQ, KENT-1, Her2, Her2 Exon 20 insert, IGF1R, Ki67, KRAS, MGMT, MGMT methylation, MSH2, MSI, NRAS, PGP (MDR1), PIK3CA, PR, PTEN, ROS1, ROS1 translocation, RRM1, SPARC, TLE3, TOPO1, TOPO2A, TS, TUBB3, VEGFR2 Cancer treatment AR, AREG, BRAF, BRCA1, cKIT, cMET, EGFR, associated markers EGFR w/T790M, EML4-ALK, ER, ERBB3, ERBB4, ERCC1, EREG, GNA11, GNAQ, Her2, Her2 Exon 20 insert, IGFR1, Ki67, KRAS, MGMT-Me, MSH2, MSI, NRAS, PGP (MDR-1), PIK3CA, PR, PTEN, ROS1 translocation, RRM1, SPARC, TLE3, TOPO1, TOPO2A, TS, TUBB3, VEGFR2 Colon cancer AREG, BRAF, EGFR, EML4-ALK, ERCC1, EREG, treatment KRAS, MSI, NRAS, PIK3CA, PTEN, associated markers TS, VEGFR2 Colon cancer AREG, BRAF, EGFR, EML4-ALK, ERCC1, EREG, treatment KRAS, MSI, NRAS, PIK3CA, PTEN, associated markers TS, VEGFR2 Melanoma BRAF, cKIT, ERBB3, ERBB4, ERCC1, GNA11, treatment GNAQ, MGMT, MGMT methylation, associated markers NRAS, PIK3CA, TUBB3, VEGFR2 Melanoma BRAF, cKIT, ERBB3, ERBB4, ERCC1, GNA11, treatment GNAQ, MGMT-Me, NRAS, PIK3CA, associated markers TUBB3, VEGFR2 Ovarian cancer BRCA1, cMET, EML4-ALK, ER, ERBB3, treatment ERCC1, KENT-1, HER2, IGF1R, PGP(MDR1), associated markers PIK3CA, PR, PTEN, RRM1, TLE3, TOPO1, TOPO2A, TS Ovarian cancer BRCA1, cMET, EML4-ALK (translocation), ER, treatment ERBB3, ERCC1, HER2, PIK3CA, PR, associated markers PTEN, RRM1, TLE3, TS Breast cancer BRAF, BRCA1, EGFR, EGFR T790M, EML4-ALK, treatment ER, ERBB3, ERCC1, HER2, Ki67, associated markers PGP (MDR1), PIK3CA, PR, PTEN, ROS1, ROS1 translocation, RRM1, TLE3, TOPO1, TOPO2A, TS Breast cancer BRAF, BRCA1, EGFR w/T790M, EML4-ALK, ER, treatment ERBB3, ERCC1, HER2, Ki67, KRAS, associated markers PIK3CA, PR, PTEN, ROS1 translocation, RRM1, TLE3, TOPO1, TOPO2A, TS NSCLC cancer BRAF, BRCA1, cMET, EGFR, EGFR w/T790M, treatment EML4-ALK, ERCC1, Her2 Exon 20 associated markers insert, KRAS, MSH2, PIK3CA, PTEN, ROS1 (trans), RRM1, TLE3, TS, VEGFR2 NSCLC cancer BRAF, cMET, EGFR, EGFR w/T790M, treatment EML4-ALK, ERCC1, Her2 Exon 20 insert, KRAS, associated markers MSH2, PIK3CA, PTEN, ROS1 translocation, RRM1, TLE3, TS Mutated in cancers AKT1, ALK, APC, ATM, BRAF, CDH1, CDKN2A, c-Kit, C-Met, CSF1R, CTNNB1, EGFR, ERBB2, ERBB4, FBXW7, FGFR1, FGFR2, FGFR3, FLT3, GNA11, GNAQ, GNAS, HNF1A, HRAS, IDH1, JAK2, JAK3, KDR, KRAS, MLH1, MPL, NOTCH1, NPM1, NRAS, PDGFRA, PIK3CA, PTEN, PTPN11, RB1, RET, SMAD4, SMARCB1, SMO, SRC, STK11, TP53, VHL Mutated in cancers ALK, BRAF, BRCA1, BRCA2, EGFR, ERRB2, GNA11, GNAQ, IDH1, IDH2, KIT, KRAS, MET, NRAS, PDGFRA, PIK3CA, PTEN, RET, SRC, TP53 Mutated in cancers AKT1, HRAS, GNAS, MEK1, MEK2, ERK1, ERK2, ERBB3, CDKN2A, PDGFRB, IFG1R, FGFR1, FGFR2, FGFR3, ERBB4, SMO, DDR2, GRB1, PTCH, SHH, PD1, UGT1A1, BIM, ESR1, MLL, AR, CDK4, SMAD4 Mutated in cancers ABL, APC, ATM, CDH1, CSFR1, CTNNB1, FBXW7, FLT3, HNF1A, JAK2, JAK3, KDR, MLH1, MPL, NOTCH1, NPM1, PTPN11, RB1, SMARCB1, STK11, VHL Mutated in cancers ABL1, AKT1, AKT2, AKT3, ALK, APC, AR, ARAF, ARFRP1, ARID1A, ARID2, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXL, BAP1, BARD1, BCL2, BCL2L2, BCL6, BCOR, BCORL1, BLM, BRAF, BRCA1, BRCA2, BRIP1, BTK, CARD11, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD79A, CD79B, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CEBPA, CHEK1, CHEK2, CIC, CREBBP, CRKL, CRLF2, CSF1R, CTCF, CTNNA1, CTNNB1, DAXX, DDR2, DNMT3A, DOT1L, EGFR, EMSY (C11orf30), EP300, EPHA3, EPHA5, EPHB1, ERBB2, ERBB3, ERBB4, ERG, ESR1, EZH2, FAM123B (WTX), FAM46C, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCL, FBXW7, FGF10, FGF14, FGF19, FGF23, FGF3, FGF4, FGF6, FGFR1, FGFR2, FGFR3, FGFR4, FLT1, FLT3, FLT4, FOXL2, GATA1, GATA2, GATA3, GID4 (C17orf39), GNA11, GNA13, GNAQ, GNAS, GPR124, GRIN2A, GSK3B, HGF, HRAS, IDH1, IDH2, IGF1R, IKBKE, IKZF1, IL7R, INHBA, IRF4, IRS2, JAK1, JAK2, JAK3, JUN, KAT6A (MYST3), KDM5A, KDM5C, KDM6A, KDR, KEAP1, KIT, KLHL6, KRAS, LRP1B, MAP2K1, MAP2K2, MAP2K4, MAP3K1, MCL1, MDM2, MDM4, MED12, MEF2B, MEN1, MET, MITF, MLH1, MLL, MLL2, MPL, MRE11A, MSH2, MSH6, MTOR, MUTYH, MYC, MYCL1, MYCN, MYD88, NF1, NF2, NFE2L2, NFKBIA, NKX2-1, NOTCH1, NOTCH2, NPM1, NRAS, NTRK1, NTRK2, NTRK3, NUP93, PAK3, PALB2, PAX5, PBRM1, PDGFRA, PDGFRB, PDK1, PIK3CA, PIK3CG, PIK3R1, PIK3R2, PPP2R1A, PRDM1, PRKAR1A, PRKDC, PTCH1, PTEN, PTPN11, RAD50, RAD51, RAF1, RARA, RB1, RET, RICTOR, RNF43, RPTOR, RUNX1, SETD2, SF3B1, SMAD2, SMAD4, SMARCA4, SMARCB1, SMO, SOCS1, SOX10, SOX2, SPEN, SPOP, SRC, STAG2, STAT4, STK11, SUFU, TET2, TGFBR2, TNFAIP3, TNFRSF14, TOP1, TP53, TSC1, TSC2, TSHR, VHL, WISP3, WT1, XPO1, ZNF217, ZNF703 Gene ALK, BCR, BCL2, BRAF, EGFR, ETV1, rearrangement in ETV4, ETV5, ETV6, EWSR1, MLL, MYC, cancer NTRK1, PDGFRA, RAF1, RARA, RET, ROS1, TMPRSS2 Cancer Related ABL1, ACE2, ADA, ADH1C, ADH4, AGT, AKT1, AKT2, AKT3, ALK, APC, AR, ARAF, AREG, ARFRP1, ARID1A, ARID2, ASNS, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXL, BAP1, BARD1, BCL2, BCL2L2, BCL6, BCOR, BCORL1, BCR, BIRC5 (survivin), BLM, BRAF, BRCA1, BRCA2, BRIP1, BTK, CA2, CARD11, CAV, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD33, CD52 (CDW52), CD79A, CD79B, CDC73, CDH1, CDK12, CDK2, CDK4, CDK6, CDK8, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CEBPA, CES2, CHEK1, CHEK2, CIC, CREBBP, CRKL, CRLF2, CSF1R, CTCF, CTNNA1, CTNNB1, DAXX, DCK, DDR2, DHFR, DNMT1, DNMT3A, DNMT3B, DOT1L, EGFR, EMSY (C11orf30), EP300, EPHA2, EPHA3, EPHA5, EPHB1, ERBB2, ERBB3, ERBB4, ERBB2 (typo?), ERCC3, EREG, ERG, ESR1, ETV1, ETV4, ETV5, ETV6, EWSR1, EZH2, FAM123B (WTX), FAM46C, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCL, FBXW7, FGF10, FGF14, FGF19, FGF23, FGF3, FGF4, FGF6, FGFR1, FGFR2, FGFR3, FGFR4, FLT1, FLT3, FLT4, FOLR1, FOLR2, FOXL2, FSHB, FSHPRH1, FSHR, GART, GATA1, GATA2, GATA3, GID4 (C17orf39), GNA11, GNA13, GNAQ, GNAS, GNRH1, GNRHR1, GPR124, GRIN2A, GSK3B, GSTP1, HDAC1, HGF, HIG1, HNF1A, HRAS, HSPCA (HSP90), IDH1, IDH2, IGF1R, IKBKE, IKZF1, IL13RA1, IL2, IL2RA (CD25), IL7R, INHBA, IRF4, IRS2, JAK1, JAK2, JAK3, JUN, KAT6A (MYST3), KDM5A, KDMSC, KDM6A, KDR (VEGFR2), KEAP1, KIT, KLHL6, KRAS, LCK, LRP1B, LTB, LTBR, MAP2K1, MAP2K2, MAP2K4, MAP3K1, MAPK, MCL1, MDM2, MDM4, MED12, MEF2B, MEN1, MET, MGMT, MITF, MLH1, MLL, MLL2, MPL, MRE11A, MS4A1 (CD20), MSH2, MSH6, MTAP, MTOR, MUTYH, MYC, MYCL1, MYCN, MYD88, NF1, NF2, NFE2L2, NFKB1, NFKB2, NFKBIA, NGF, NKX2-1, NOTCH1, NOTCH2, NPM1, NRAS, NTRK1, NTRK2, NTRK3, NUP93, ODC1, OGFR, PAK3, PALB2, PAX5, PBRM1, PDGFC, PDGFRA, PDGFRB, PDK1, PGP, PGR (PR), PIK3CA, PIK3CG, PIK3R1, PIK3R2, POLA, PPARG, PPARGC1, PPP2R1A, PRDM1, PRKAR1A, PRKDC, PTCH1, PTEN, PTPN11, RAD50, RAD51, RAF1, RARA, RBI, RET, RICTOR, RNF43, ROS1, RPTOR, RRM1, RRM2, RRM2B, RUNX1, RXR, RXRB, RXRG, SETD2, SF3B1, SMAD2, SMAD4, SMARCA4, SMARCB1, SMO, SOCS1, SOX10, SOX2, SPARC, SPEN, SPOP, SRC, SST, SSTR1, SSTR2, SSTR3, SSTR4, SSTR5, STAG2, STAT4, STK11, SUFU, TET2, TGFBR2, TK1, TLE3, TMPRSS2, TNF, TNFAIP3, TNFRSF14, TOP1, TOP2, TOP2A, TOP2B, TP53, TS, TSC1, TSC2, TSHR, TUBB3, TXN, TYMP, VDR, VEGF (VEGFA), VEGFC, VHL, WISP3, WT1, XDH, XPO1, YES1, ZAP70, ZNF217, ZNF703 Cytohesions cytohesin-1 (CYTH1), cytohesin-2 (CYTH2; ARNO), cytohesin-3 (CYTH3; Grp1; ARNO3), cytohesin-4 (CYTH4) Cancer/Angio Erb 2, Erb 3, Erb 4, UNC93a, B7H3, MUC1, MUC2, MUC16, MUC17, 5T4, RAGE, VEGF A, VEGFR2, FLT1, DLL4, Epcam Tissue (Breast) BIG H3, GCDFP-15, PR(B), GPR 30, CYFRA 21, BRCA 1, BRCA 2, ESR 1, ESR2 Tissue (Prostate) PSMA, PCSA, PSCA, PSA, TMPRSS2 Inflammation/ MFG-E8, IFNAR, CD40, CD80, MICB, Immune HLA-DRb, IL-17-Ra Common vesicle HSPA8, CD63, Actb, GAPDH, CD9, CD81, markers ANXA2, HSP90AA1, ENO1, YWHAZ, PDCD6IP, CFL1, SDCBP, PKN2, MSN, MFGE8, EZR, YWHAG, PGK1, EEF1A1, PPIA, GLC1F, GK, ANXA6, ANXA1, ALDOA, ACTG1, TPI1, LAMP2, HSP90AB1, DPP4, YWHAB, TSG101, PFN1, LDHB, HSPA1B, HSPA1A, GSTP1, GNAI2, GDI2, CLTC, ANXAS, YWHAQ, TUBA1A, THBS1, PRDX1, LDHA, LAMP1, CLU, CD86 Common vesicle CD63, GAPDH, CD9, CD81, ANXA2, ENO1, membrane SDCBP, MSN, MFGE8, EZR, GK, ANXA1, markers LAMP2, DPP4, TSG101, HSPA1A, GDI2, CLTC, LAMP1, CD86, ANPEP, TFRC, SLC3A2, RDX, RAP1B, RAB5C, RAB5B, MYH9, ICAM1, FN1, RAB11B, PIGR, LGALS3, ITGB1, EHD1, CLIC1, ATP1A1, ARF1, RAP1A, P4HB, MUC1, KRT10, HLA- A, FLOT1, CD59, C1orf58, BASP1, TACSTD1, STOM Common vesicle MHC class I, MHC class II, Integrins, Alpha 4 markers beta 1, Alpha M beta 2, Beta 2, ICAM1/CD54, P-selection, Dipeptidylpeptidase IV/CD26, Aminopeptidase n/CD13, CD151, CD53, CD37, CD82, CD81, CD9, CD63, Hsp70, Hsp84/90 Actin, Actin-binding proteins, Tubulin, Annexin I, Annexin II, Annexin IV, Annexin V, Annexin VI, RAB7/RAP1B/RADGDI, Gi2alpha/14-3-3, CBL/LCK, CD63, GAPDH, CD9, CD81, ANXA2, ENO1, SDCBP, MSN, MFGE8, EZR, GK, ANXA1, LAMP2, DPP4, TSG101, HSPA1A, GDI2, CLTC, LAMP1, Cd86, ANPEP, TFRC, SLC3A2, RDX, RAP1B, RAB5C, RAB5B, MYH9, ICAM1, FN1, RAB11B, PIGR, LGALS3, ITGB1, EHD1, CLIC1, ATP1A1, ARF1, RAP1A, P4HB, MUC1, KRT10, HLA-A, FLOT1, CD59, C1orf58, BASP1, TACSTD1, STOM Vesicle markers A33, a33 n15, AFP, ALA, ALIX, ALP, AnnexinV, APC, ASCA, ASPH (246-260), ASPH (666-680), ASPH (A-10), ASPH (D01P), ASPH (D03), ASPH (G-20), ASPH (H-300), AURKA, AURKB, B7H3, B7H4, BCA-225, BCNP, BDNF, BRCA, CA125 (MUC16), CA- 19-9, C-Bir, CD1.1, CD10, CD174 (Lewis y), CD24, CD44, CD46, CD59 (MEM-43), CD63, CD66e CEA, CD73, CD81, CD9, CDA, CDAC1 1a2, CEA, C-Erb2, C-erbB2, CRMP-2, CRP, CXCL12, CYFRA21-1, DLL4, DR3, EGFR, Epcam, EphA2, EphA2 (H-77), ER, ErbB4, EZH2, FASL, FRT, FRT c.f23, GDF15, GPCR, GPR30, Gro-alpha, HAP, HBD 1, HBD2, HER 3 (ErbB3), HSP, HSP70, hVEGFR2, iC3b, IL 6 Unc, IL-1B, IL6 Unc, IL6R, IL8, IL-8, INSIG-2, KLK2, L1CAM, LAMN, LDH, MACC-1, MAPK4, MART-1, MCP-1, M-CSF, MFG-E8, MIC1, MIF, MIS RII, MMG, MMP26, MMP7, MMP9, MS4A1, MUC1, MUC1 seq1, MUC1 seq11A, MUC17, MUC2, Ncam, NGAL, NPGP/NPFF2, OPG, OPN, p53, p53, PA2G4, PBP, PCSA, PDGFRB, PGP9.5, PIM1, PR (B), PRL, PSA, PSMA, PSME3, PTEN, R5-CD9 Tube 1, Reg IV, RUNX2, SCRN1, seprase, SERPINB3, SPARC, SPB, SPDEF, SRVN, STAT 3, STEAP1, TF (FL-295), TFF3, TGM2, TIMP-1, TIMP1, TIMP2, TMEM211, TMPRSS2, TNF-alpha, Trail-R2, Trail-R4, TrKB, TROP2, Tsg 101, TWEAK, UNC93A, VEGF A, YPSMA-1 Vesicle markers NSE, TRIM29, CD63, CD151, ASPH, LAMP2, TSPAN1, SNAIL, CD45, CKS1, NSE, FSHR, OPN, FTH1, PGP9, ANNEXIN 1, SPD, CD81, EPCAM, PTH1R, CEA, CYTO 7, CCL2, SPA, KRAS, TWIST1, AURKB, MMP9, P27, MMP1, HLA, HIF, CEACAM, CENPH, BTUB, INTG b4, EGFR, NACC1, CYTO 18, NAP2, CYTO 19, ANNEXIN V, TGM2, ERB2, BRCA1, B7H3, SFTPC, PNT, NCAM, MS4A1, P53, INGA3, MUC2, SPA, OPN, CD63, CD9, MUC1, UNCR3, PAN ADH, HCG, TIMP, PSMA, GPCR, RACK1, PSCA, VEGF, BMP2, CD81, CRP, PRO GRP, B7H3, MUC1, M2PK, CD9, PCSA, PSMA Vesicle markers TFF3, MS4A1, EphA2, GAL3, EGFR, N-gal, PCSA, CD63, MUC1, TGM2, CD81, DR3, MACC-1, TrKB, CD24, TIMP-1, A33, CD66 CEA, PRL, MMP9, MMP7, TMEM211, SCRN1, TROP2, TWEAK, CDACC1, UNC93A, APC, C-Erb, CD10, BDNF, FRT, GPR30, P53, SPR, OPN, MUC2, GRO-1, tsg 101, GDF15 Vesicle markers CD9, Erb2, Erb4, CD81, Erb3, MUC16, CD63, DLL4, HLA-Drpe, B7H3, IFNAR, 5T4, PCSA, MICB, PSMA, MFG-E8, Muc1, PSA, Muc2, Unc93a, VEGFR2, EpCAM, VEGF A, TMPRSS2, RAGE, PSCA, CD40, Muc17, IL-17-RA, CD80 Benign Prostate BCMA, CEACAM-1, HVEM, IL-1 R4, IL-10 Rb, Hyperplasia Trappin-2, p53, hsa-miR-329, hsa-miR- (BPH) 30a, hsa-miR-335, hsa-miR-152, hsa-miR-151-5p, hsa-miR-200a, hsa-miR-145, hsa-miR- 29a, hsa-miR-106b, hsa-miR-595, hsa-miR-142-5p, hsa-miR-99a, hsa-miR-20b, hsa-miR- 373, hsa-miR-502-5p, hsa-miR-29b, hsa-miR- 142-3p, hsa-miR-663, hsa-miR-423-5p, hsa- miR-15a, hsa-miR-888, hsa-miR-361-3p, hsa- miR-365, hsa-miR-10b, hsa-miR-199a-3p, hsa- miR-181a, hsa-miR-19a, hsa-miR-125b, hsa-miR- 760, hsa-miR-7a, hsa-miR-671-5p, hsa- miR-7c, hsa-miR-1979, hsa-miR-103 Metastatic hsa-miR-100, hsa-miR-1236, hsa-miR-1296, Prostate hsa-miR-141, hsa-miR-146b-5p, hsa-miR-17*, Cancer hsa-miR-181a, hsa-miR-200b, hsa-miR-20a*, hsa-miR-23a*, hsa-miR-331-3p, hsa-miR-375, hsa-miR-452, hsa-miR-572, hsa-miR-574-3p, hsa-miR-577, hsa-miR-582-3p, hsa-miR-937, miR-10a, miR-134, miR-141, miR-200b, miR-30a, miR-32, miR-375, miR-495, miR-564, miR-570, miR-574-3p, miR-885-3p Metastatic Prostate hsa-miR-200b, hsa-miR-375, hsa-miR-141, Cancer hsa-miR-331-3p, hsa-miR-181a, hsa-miR-574-3p Prostate Cancer hsa-miR-574-3p, hsa-miR-141, hsa-miR-432, hsa-miR-326, hsa-miR-2110, hsa-miR-181a- 2*, hsa-miR-107, hsa-miR-30 1 a, hsa-miR-484, hsa-miR-625* Metastatic Prostate hsa-miR-582-3p, hsa-miR-20a*, hsa-miR-375, Cancer hsa-miR-200b, hsa-miR-379, hsa-miR-572, hsa-miR-513a-5p, hsa-miR-577, hsa-miR-23a*, hsa-miR-1236, hsa-miR-609, hsa-miR-17*, hsa-miR-130b, hsa-miR-619, hsa-miR-624*, hsa-miR-198 Metastatic Prostate FOX01A, SOX9, CLNS1A, PTGDS, XPO1, Cancer LETMD1, RAD23B, ABCC3, APC, CHES1, EDNRA, FRZB, HSPG2, TMPRSS2_ETV1 fusion Prostate Cancer hsa-let-7b, hsa-miR-107, hsa-miR-1205, hsa- miR-1270, hsa-miR-130b, hsa-miR-141, hsa- miR-143, hsa-miR-148b*, hsa-miR-150, hsa- miR-154*, hsa-miR-181a*, hsa-miR-181a-2*, hsa-miR-18a*, hsa-miR-19b-1*, hsa-miR-204, hsa-miR-2110, hsa-miR-215, hsa-miR-217, hsa-miR-219-2-3p, hsa-miR-23b*, hsa-miR- 299-5p, hsa-miR-301a, hsa-miR-301a, hsa-miR- 326, hsa-miR-331-3p, hsa-miR-365*, hsa- miR-373*, hsa-miR-424, hsa-miR-424*, hsa-miR- 432, hsa-miR-450a, hsa-miR-451, hsa-miR- 484, hsa-miR-497, hsa-miR-517*, hsa-miR-517a, hsa-miR-518f, hsa-miR-574-3p, hsa-miR-595, hsa-miR-617, hsa-miR-625*, hsa-miR-628-5p, hsa-miR-629, hsa-miR-634, hsa-miR-769-5p, hsa-miR-93, hsa-miR-96 Prostate Cancer CD9, PSMA, PCSA, CD63, CD81, B7H3, IL 6, OPG-13, IL6R, PA2G4, EZH2, RUNX2, SERPINB3, EpCam Prostate Cancer A33, a33 n15, AFP, ALA, ALIX, ALP, AnnexinV, APC, ASCA, ASPH (246-260), ASPH (666-680), ASPH (A-10), ASPH (D01P), ASPH (D03), ASPH (G-20), ASPH (H-300), AURKA, AURKB, B7H3, B7H4, BCA-225, BCNP, BDNF, BRCA, CA125 (MUC16), CA- 19-9, C-Bir, CD1.1, CD10, CD174 (Lewis y), CD24, CD44, CD46, CD59 (MEM-43), CD63, CD66e CEA, CD73, CD81, CD9, CDA, CDAC1 1a2, CEA, C-Erb2, C-erbB2, CRMP-2, CRP, CXCL12, CYFRA21-1, DLL4, DR3, EGFR, Epcam, EphA2, EphA2 (H-77), ER, ErbB4, EZH2, FASL, FRT, FRT c.f23, GDF15, GPCR, GPR30, Gro-alpha, HAP, HBD 1, HBD2, HER 3 (ErbB3), HSP, HSP70, hVEGFR2, iC3b, IL 6 Unc, IL-1B, IL6 Unc, IL6R, IL8, IL-8, INSIG-2, KLK2, L1CAM, LAMN, LDH, MACC-1, MAPK4, MART-1, MCP-1, M-CSF, MFG-E8, MIC1, MIF, MIS RII, MMG, MMP26, MMP7, MMP9, MS4A1, MUC1, MUC1 seq1, MUC1 seq11A, MUC17, MUC2, Ncam, NGAL, NPGP/NPFF2, OPG, OPN, p53, p53, PA2G4, PBP, PCSA, PDGFRB, PGP9.5, PIM1, PR (B), PRL, PSA, PSMA, PSME3, PTEN, R5-CD9 Tube 1, Reg IV, RUNX2, SCRN1, seprase, SERPINB3, SPARC, SPB, SPDEF, SRVN, STAT 3, STEAP1, TF (FL-295), TFF3, TGM2, TIMP-1, TIMP1, TIMP2, TMEM211, TMPRSS2, TNF-alpha, Trail-R2, Trail-R4, TrKB, TROP2, Tsg 101, TWEAK, UNC93A, VEGF A, YPSMA-1 Prostate Cancer 5T4, ACTG1, ADAM10, ADAM15, ALDOA, Vesicle Markers ANXA2, ANXA6, APOA1, ATP1A1, BASP1, C1orf58, C20orf114, C8B, CAPZA1, CAV1, CD151, CD2AP, CD59, CD9, CD9, CFL1, CFP, CHMP4B, CLTC, COTL1, CTNND1, CTSB, CTSZ, CYCS, DPP4, EEF1A1, EHD1, ENO1, F11R, F2, F5, FAM125A, FNBP1L, FOLH1, GAPDH, GLB1, GPX3, HIST1H1C, HIST1H2AB, HSP90AB1, HSPA1B, HSPA8, IGSF8, ITGB1, ITIH3, JUP, LDHA, LDHB, LUM, LYZ, MFGE8, MGAM, MMP9, MYH2, MYL6B, NME1, NME2, PABPC1, PABPC4, PACSIN2, PCBP2, PDCD6IP, PRDX2, PSA, PSMA, PSMA1, PSMA2, PSMA4, PSMA6, PSMA7, PSMB1, PSMB2, PSMB3, PSMB4, PSMB5, PSMB6, PSMB8, PTGFRN, RPS27A, SDCBP, SERINC5, SH3GL1, SLC3A2, SMPDL3B, SNX9, TACSTD1, TCN2, THBS1, TPI1, TSG101, TUBB, VDAC2, VPS37B, YWHAG, YWHAQ, YWHAZ Prostate Cancer FLNA, DCRN, HER 3 (ErbB3), VCAN, CD9, Vesicle Markers GAL3, CDADC1, GM-CSF, EGFR, RANK, CSA, PSMA, ChickenIgY, B7H3, PCSA, CD63, CD3, MUC1, TGM2, CD81, S100-A4, MFG-E8, Integrin, NK-2R(C-21), PSA, CD24, TIMP-1, IL6 Unc, PBP, PIM1, CA-19-9, Trail-R4, MMP9, PRL, EphA2, TWEAK, NY-ESO-1, Mammaglobin, UNC93A, A33, AURKB, CD41, XAGE-1, SPDEF, AMACR, seprase/FAP, NGAL, CXCL12, FRT, CD66e CEA, SIM2 (C-15), C-Bir, STEAP, PSIP1/LEDGF, MUC17, hVEGFR2, ERG, MUC2, ADAM10, ASPH (A-10), CA125, Gro-alpha, Tsg 101, SSX2, Trail-R4 Prostate Cancer NT5E (CD73), A33, ABL2, ADAM10, AFP, ALA, Vesicle Markers ALIX, ALPL, AMACR, Apo J/CLU, ASCA, ASPH (A-10), ASPH (D01P), AURKB, B7H3, B7H4, BCNP, BDNF, CA125 (MUC16), CA-19-9, C-Bir (Flagellin), CD10, CD151, CD24, CD3, CD41, CD44, CD46, CD59(MEM-43), CD63, CD66e CEA, CD81, CD9, CDA, CDADC1, C-erbB2, CRMP-2, CRP, CSA, CXCL12, CXCR3, CYFRA21-1, DCRN, DDX-1, DLL4, EGFR, EpCAM, EphA2, ERG, EZH2, FASL, FLNA, FRT, GAL3, GATA2, GM-CSF, Gro-alpha, HAP, HER3 (ErbB3), HSP70, HSPB1, hVEGFR2, iC3b, IL-1B, IL6 R, IL6 Unc, IL7 R alpha/CD127, IL8, INSIG-2, Integrin, KLK2, Label, LAMN, Mammaglobin, M-CSF, MFG- E8, MIF, MIS RII, MMP7, MMP9, MS4A1, MUC1, MUC17, MUC2, Ncam, NDUFB7, NGAL, NK-2R(C-21), NY-ESO-1, p53, PBP, PCSA, PDGFRB, PIM1, PRL, PSA, PSIP1/LEDGF, PSMA, RAGE, RANK, Reg IV, RUNX2, S100-A4, seprase/FAP, SERPINB3, SIM2 (C-15), SPARC, SPC, SPDEF, SPP1, SSX2, SSX4, STEAP, STEAP4, TFF3, TGM2, TIMP-1, TMEM211, Trail-R2, Trail-R4, TrKB (poly), Trop2, Tsg 101, TWEAK, UNC93A, VCAN, VEGF A, wnt-5a(C-16), XAGE, XAGE-1 Prostate Vesicle ADAM 9, ADAM10, AGR2, ALDOA, ALIX, Membrane ANXA1, ANXA2, ANXA4, ARF6, ATP1A3, B7H3, BCHE, BCL2L14 (Bcl G), BCNP1, BDKRB2, BDNFCAV1-Caveolin1, CCR2 (CC chemokine receptor 2, CD192), CCR5 (CC chemokine receptor 5), CCT2 (TCP1-beta), CD10, CD151, CD166/ALCAM, CD24, CD283/TLR3, CD41, CD46, CD49d (Integrin alpha 4, ITGA4), CD63, CD81, CD9, CD90/THY1, CDH1, CDH2, CDKN1A cyclin-dependent kinase inhibitor (p21), CGA gene (coding for the alpha subunit of glycoprotein hormones), CLDN3-Claudin3, COX2 (PTGS2), CSE1L (Cellular Apoptosis Susceptibility), CXCR3, Cytokeratin 18, Eag1 (KCNH1), EDIL3 (del-1), EDNRB-Endothelial Receptor Type B, EGFR, EpoR, EZH2 (enhancer of Zeste Homolog2), EZR, FABP5, Farnesyltransferase/geranylgeranyl diphosphate synthase 1 (GGPS1), Fatty acid synthase (FASN), FTL (light and heavy), GAL3, GDF15-Growth Differentiation Factor 15, GloI, GM- CSF, GSTP1, H3F3A, HGF (hepatocyte growth factor), hK2/Kif2a, HSP90AA1, HSPA1A/ HSP70-1, HSPB1, IGFBP-2, IGFBP-3, ILlalpha, IL-6, IQGAP1, ITGAL (Integrin alpha L chain), Ki67, KLK1, KLK10, KLK11, KLK12, KLK13, KLK14, KLK15, KLK4, KLK5, KLK6, KLK7, KLK8, KLK9, Lamp-2, LDH-A, LGALS3BP, LGALS8, MMP 1, MMP 2, MMP 25, MMP 3, MMP10, MMP-14/MT1- MMP, MMP7, MTA1nAnS, Nav1.7, NKX3-1, Notch1, NRP1/CD304, PAP (ACPP), PGP, PhIP, PIP3/BPNT1, PKM2, PKP1 (plakophilin1), PKP3 (plakophilin3), Plasma chromogranin-A (CgA), PRDX2, Prostate secretory protein (PSP94)/P-Microseminoprotein (MSP)/IGBF, PSAP, PSMA, PSMA1, PTENPTPN13/PTPL1, RPL19, seprase/ FAPSET, SLC3A2/CD98, SRVN, STEAP1, Syndecan/CD138, TGFB, TGM2, TIMP-1TLR4 (CD284), TLR9 (CD289), TMPRSS1/ hepsin, TMPRSS2, TNFR1, TNFα, Transferrin receptor/CD71/TRFR, Trop2 (TACSTD2), TWEAK uPA (urokinase plasminoge activator) degrades extracellular matrix, uPAR (uPA receptor)/CD87, VEGFR1, VEGFR2 Prostate Vesicle ADAM 34, ADAM 9, AGR2, ALDOA, ANXA1, Markers ANXA 11, ANXA4, ANXA 7, ANXA2, ARF6, ATP1A1, ATP1A2, ATP1A3, BCHE, BCL2L14 (Bcl G), BDKRB2, CA215, CAV1- Caveolin1, CCR2 (CC chemokine receptor 2, CD192), CCR5 (CC chemokine receptor 5), CCT2 (TCP1-beta), CD166/ALCAM, CD49b (Integrin alpha 2, ITGA4), CD90/THY1, CDH1, CDH2, CDKN1A cyclin-dependent kinase inhibitor (p21), CGA gene (coding for the alpha subunit of glycoprotein hormones), CHMP4B, CLDN3-Claudin3, CLSTN1 (Calsyntenin-1), COX2 (PTGS2), CSE1L (Cellular Apoptosis Susceptibility), Cytokeratin 18, Eag1 (KCNH1) (plasma membrane-K+-voltage gated channel), EDIL3 (del-1), EDNRB- Endothelial Receptor Type B, Endoglin/CD105, ENOX2-Ecto-NOX disulphide Thiol exchanger 2, EPCA-2 Early prostate cancer antigen2, EpoR, EZH2 (enhancer of Zeste Homolog2), EZR, FABP5, Farnesyltransferase/ geranylgeranyl diphosphate synthase 1 (GGPS1), Fatty acid synthase (FASN, plasma membrane protein), FTL (light and heavy), GDF15-Growth Differentiation Factor 15, GloI, GSTP1, H3F3A, HGF (hepatocyte growth factor), hK2 (KLK2), HSP90AA1, HSPA1A/ HSP70-1, IGFBP-2, IGFBP-3, ILlalpha, IL-6, IQGAP1, ITGAL (Integrin alpha L chain), Ki67, KLK1, KLK10, KLK11, KLK12, KLK13, KLK14, KLK15, KLK4, KLK5, KLK6, KLK7, KLK8, KLK9, Lamp-2, LDH-A, LGALS3BP, LGALS8, MFAP5, MMP 1, MMP 2, MMP 24, MMP 25, MMP 3, MMP10, MMP-14/MT1-MMP, MTA1, nAnS, Nav1.7, NCAM2-Neural cell Adhesion molecule 2, NGEP/D-TMPP/IPCA-5/ANO7, NKX3-1, Notch1, NRP1/CD304, PGP, PAP (ACPP), PCA3-Prostate cancer antigen 3, Pdia3/ ERp57, PhIP, phosphatidylethanolamine (PE), PIP3, PKP1 (plakophilin1), PKP3 (plakophilin3), Plasma chromogranin-A (CgA), PRDX2, Prostate secretory protein (PSP94)/β-Microseminoprotein (MSP)/IGBF, PSAP, PSMA1, PTEN, PTGFRN, PTPN13/PTPL1, PKM2, RPL19, SCA-1/ATXN1, SERINC5/TPO1, SET, SLC3A2/CD98, STEAP1, STEAP-3, SRVN, Syndecan/CD138, TGFB, Tissue Polypeptide Specific antigen TPS, TLR4 (CD284), TLR9 (CD289), TMPRSS1/hepsin, TMPRSS2, TNFR1, TNFα, CD283/TLR3, Transferrin receptor/CD71/TRFR, uPA (urokinase plasminoge activator), uPAR (uPA receptor)/CD87, VEGFR1, VEGFR2 Prostate Cancer hsa-miR-1974, hsa-miR-27b, hsa-miR-103, Treatment hsa-miR-146a, hsa-miR-22, hsa-miR-382, hsa- miR-23a, hsa-miR-376c, hsa-miR-335, hsa-miR- 142-5p, hsa-miR-221, hsa-miR-142-3p, hsa- miR-151-3p, hsa-miR-21, hsa-miR-16 Prostate Cancer let-7d, miR-148a, miR-195, miR-25, miR-26b, miR-329, miR-376c, miR-574-3p, miR-888, miR-9, miR1204, miR-16-2*, miR-497, miR-588, miR-614, miR-765, miR92b*, miR-938, let-7f-2*, miR-300, miR-523, miR-525-5p, miR-1182, miR-1244, miR-520d-3p, miR-379, let-7b, miR-125a-3p, miR-1296, miR-134, miR-149, miR-150, miR-187, miR-32, miR-324- 3p, miR-324-5p, miR-342-3p, miR-378, miR- 378*, miR-384, miR-451, miR-455-3p, miR- 485-3p, miR-487a, miR-490-3p, miR-502-5p, miR-548a-5p, miR-550, miR-562, miR-593, miR-593*, miR-595, miR-602, miR-603, miR-654-5p, miR-877*, miR-886-5p, miR-125a-5p, miR-140-3p, miR-192, miR-196a, miR-2110, miR-212, miR-222, miR-224*, miR-30b*, miR-499-3p, miR-505* Prostate (PCSA + miR-182, miR-663, miR-155, mirR-125a-5p, cMVs) miR-548a-5p, miR-628-5p, miR-517*, miR- 450a, miR-920, hsa-miR-619, miR-1913, miR-224*, miR-502-5p, miR-888, miR-376a, miR- 542-5p, miR-30b*, miR-1179 Prostate Cancer miR-183-96-182 cluster (miRs-183, 96 and 182), metal ion transporter such as hZIP1, SLC39A1, SLC39A2, SLC39A3, SLC39A4, SLC39A5, SLC39A6, SLC39A7, SLC39A8, SLC39A9, SLC39A10, SLC39A11, SLC39A12, SLC39A13, SLC39A14 Prostate Cancer RAD23B, FBP1, TNFRSF1A, CCNG2, NOTCH3, ETV1, BID, SIM2, LETMD1, ANXA1, miR-519d, miR-647 Prostate Cancer RAD23B, FBP1, TNFRSF1A, NOTCH3, ETV1, BID, SIM2, ANXA1, BCL2 Prostate Cancer ANPEP, ABL1, PSCA, EFNA1, HSPB1, INMT, TRIP13 Prostate Cancer E2F3, c-met, pRB, EZH2, e-cad, CAXII, CAIX, HIF-1α, Jagged, PIM-1, hepsin, RECK, Clusterin, MMP9, MTSP-1, MMP24, MMP15, IGFBP-2, IGFBP-3, E2F4, caveolin, EF-1A, Kallikrein 2, Kallikrein 3, PSGR Prostate Cancer A2ML1, BAX, C10orf47, C1orf162, CSDA, EIFC3, ETFB, GABARAPL2, GUK1, GZMH, HIST1H3B, HLA-A, HSP90AA1, NRGN, PRDX5, PTMA, RABAC1, RABAGAP1L, RPL22, SAP18, SEPW1, SOX1 Prostate Cancer NY-ESO-1, SSX-2, SSX-4, XAGE-1b, AMACR, p90 autoantigen, LEDGF Prostate Cancer A33, ABL2, ADAM10, AFP, ALA, ALIX, ALPL, ApoJ/CLU, ASCA, ASPH(A-10), ASPH(D01P), AURKB, B7H3, B7H3, B7H4, BCNP, BDNF, CA125(MUC16), CA-19-9, C- Bir, CD10, CD151, CD24, CD41, CD44, CD46, CD59(MEM-43), CD63, CD63, CD66eCEA, CD81, CD81, CD9, CD9, CDA, CDADC1, CRMP-2, CRP, CXCL12, CXCR3, CYFRA21-1, DDX-1, DLL4, DLL4, EGFR, Epcam, EphA2, ErbB2, ERG, EZH2, FASL, FLNA, FRT, GAL3, GATA2, GM-CSF, Gro-alpha, HAP, HER3(ErbB3), HSP70, HSPB1, hVEGFR2, iC3b, IL-1B, IL6R, IL6Unc, IL7Ralpha/CD127, IL8, INSIG-2, Integrin, KLK2, LAMN, Mammoglobin, M-CSF, MFG-E8, MIF, MISRII, MMP7, MMP9, MUC1, Muc1, MUC17, MUC2, Ncam, NDUFB7, NGAL, NK-2R(C-21), NT5E (CD73), p53, PBP, PCSA, PCSA, PDGFRB, PIM1, PRL, PSA, PSA, PSMA, PSMA, RAGE, RANK, RegIV, RUNX2, S100-A4, seprase/FAP, SERPINB3, SIM2(C-15), SPARC, SPC, SPDEF, SPP1, STEAP, STEAP4, TFF3, TGM2, TIMP-1, TMEM211, Trail-R2, Trail-R4, TrKB(poly), Trop2, Tsg101, TWEAK, UNC93A, VEGFA, wnt-5a(C-16) Prostate Vesicles CD9, CD63, CD81, PCSA, MUC2, MFG-E8 Prostate Cancer miR-148a, miR-329, miR-9, miR-378*, miR-25, miR-614, miR-518c*, miR-378, miR-765, let-7f-2*, miR-574-3p, miR-497, miR-32, miR-379, miR-520g, miR-542-5p, miR-342-3p, miR-1206, miR-663, miR-222 Prostate Cancer hsa-miR-877*, hsa-miR-593, hsa-miR-595, hsa-miR-300, hsa-miR-324-5p, hsa-miR-548a- 5p, hsa-miR-329, hsa-miR-550, hsa-miR-886-5p, hsa-miR-603, hsa-miR-490-3p, hsa-miR- 938, hsa-miR-149, hsa-miR-150, hsa-miR-1296, hsa-miR-384, hsa-miR-487a, hsa-miRPlus- C1089, hsa-miR-485-3p, hsa-miR-525-5p Prostate Cancer hsa-miR-451, hsa-miR-223, hsa-miR-593*, hsa-miR-1974, hsa-miR-486-5p, hsa-miR-19b, hsa-miR-320b, hsa-miR-92a, hsa-miR-21, hsa-miR-675*, hsa-miR-16, hsa-miR-876-5p, hsa- miR-144, hsa-miR-126, hsa-miR-137, hsa-miR-1913, hsa-miR-29b-1*, hsa-miR-15a, hsa- miR-93, hsa-miR-1266 Inflammatory miR-588, miR-1258, miR-16-2*, miR-938, Disease miR-526b, miR-92b*, let-7d, miR-378*, miR- 124, miR-376c, miR-26b, miR-1204, miR-574-3p, miR-195, miR-499-3p, miR-2110, miR-888 Prostate Cancer A33, ADAM10, AMACR, ASPH (A-10), AURKB, B7H3, CA125, CA-19-9, C-Bir, CD24, CD3, CD41, CD63, CD66e CEA, CD81, CD9, CDADC1, CSA, CXCL12, DCRN, EGFR, EphA2, ERG, FLNA, FRT, GAL3, GM-CSF, Gro-alpha, HER 3 (ErbB3), hVEGFR2, IL6 Unc, Integrin, Mammaglobin, MFG-E8, MMP9, MUC1, MUC17, MUC2, NGAL, NK-2R(C- 21), NY-ESO-1, PBP, PCSA, PIM1, PRL, PSA, PSIP1/LEDGF, PSMA, RANK, S100-A4, seprase/FAP, SIM2 (C-15), SPDEF, SSX2, STEAP, TGM2, TIMP-1, Trail-R4, Tsg 101, TWEAK, UNC93A, VCAN, XAGE-1 Prostate Cancer A33, ADAM10, ALIX, AMACR, ASCA, ASPH (A-10), AURKB, B7H3, BCNP, CA125, CA-19-9, C-Bir (Flagellin), CD24, CD3, CD41, CD63, CD66e CEA, CD81, CD9, CDADC1, CRP, CSA, CXCL12, CYFRA21-1, DCRN, EGFR, EpCAM, EphA2, ERG, FLNA, GAL3, GATA2, GM-CSF, Gro alpha, HER3 (ErbB3), HSP70, hVEGFR2, iC3b, IL-1B, IL6 Unc, IL8, Integrin, KLK2, Mammaglobin, MFG-E8, MMP7, MMP9, MS4A1, MUC1, MUC17, MUC2, NGAL, NK-2R(C-21), NY-ESO-1, p53, PBP, PCSA, PIM1, PRL, PSA, PSMA, RANK, RUNX2, S100-A4, seprase/FAP, SERPINB3, SIM2 (C-15), SPC, SPDEF, SSX2, SSX4, STEAP, TGM2, TIMP-1, TRAIL R2, Trail-R4, Tsg 101, TWEAK, VCAN, VEGF A, XAGE Prostate Vesicles EpCam, CD81, PCSA, MUC2, MFG-E8 Prostate Vesicles CD9, CD63, CD81, MMP7, EpCAM Prostate Cancer let-7d, miR-148a, miR-195, miR-25, miR-26b, miR-329, miR-376c, miR-574-3p, miR-888, miR-9, miR1204, miR-16-2*, miR-497, miR-588, miR-614, miR-765, miR92b*, miR-938, let-7f-2*, miR-300, miR-523, miR-525-5p, miR-1182, miR-1244, miR-520d-3p, miR-379, let-7b, miR-125a-3p, miR-1296, miR-134, miR-149, miR-150, miR-187, miR-32, miR-324- 3p, miR-324-5p, miR-342-3p, miR-378, miR-378*, miR-384, miR-451, miR-455-3p, miR- 485-3p, miR-487a, miR-490-3p, miR-502-5p, miR-548a-5p, miR-550, miR-562, miR-593, miR-593*, miR-595, miR-602, miR-603, miR-654-5p, miR-877*, miR-886-5p, miR-125a-5p, miR-140-3p, miR-192, miR-196a, miR-2110, miR-212, miR-222, miR-224*, miR-30b*, miR-499-3p, miR-505* Prostate Cancer STAT3, EZH2, p53, MACC1, SPDEF, RUNX2, YB-1, AURKA, AURKB Prostate Cancer E.001036, E.001497, E.001561, E.002330, (Ensembl ENSG E.003402, E.003756, E.004838, E.005471, identifiers) E.005882, E.005893, E.006210, E.006453, E.006625, E.006695, E.006756, E.007264, E.007952, E.008118, E.008196, E.009694, E.009830, E.010244, E.010256, E.010278, E.010539, E.010810, E.011052, E.011114, E.011143, E.011304, E.011451, E.012061, E.012779, E.014216, E.014257, E.015133, E.015171, E.015479, E.015676, E.016402, E.018189, E.018699, E.020922, E.022976, E.023909, E.026508, E.026559, E.029363, E.029725, E.030582, E.033030, E.035141, E.036257, E.036448, E.038002, E.039068, E.039560, E.041353, E.044115, E.047410, E.047597, E.048544, E.048828, E.049239, E.049246, E.049883, E.051596, E.051620, E.052795, E.053108, E.054118, E.054938, E.056097, E.057252, E.057608, E.058729, E.059122, E.059378, E.059691, E.060339, E.060688, E.061794, E.061918, E.062485, E.063241, E.063244, E.064201, E.064489, E.064655, E.064886, E.065054, E.065057, E.065308, E.065427, E.065457, E.065485, E.065526, E.065548, E.065978, E.066455, E.066557, E.067248, E.067369, E.067704, E.068724, E.068885, E.069535, E.069712, E.069849, E.069869, E.069956, E.070501, E.070785, E.070814, E.071246, E.071626, E.071859, E.072042, E.072071, E.072110, E.072506, E.073050, E.073350, E.073584, E.073756, E.074047, E.074071, E.074964, E.075131, E.075239, E.075624, E.075651, E.075711, E.075856, E.075886, E.076043, E.076248, E.076554, E.076864, E.077097, E.077147, E.077312, E.077514, E.077522, E.078269, E.078295, E.078808, E.078902, E.079246, E.079313, E.079785, E.080572, E.080823, E.081087, E.081138, E.081181, E.081721, E.081842, E.082212, E.082258, E.082556, E.083093, E.083720, E.084234, E.084463, E.085224, E.085733, E.086062, E.086205, E.086717, E.087087, E.087301, E.088888, E.088899, E.088930, E.088992, E.089048, E.089127, E.089154, E.089177, E.089248, E.089280, E.089902, E.090013, E.090060, E.090565, E.090612, E.090615, E.090674, E.090861, E.090889, E.091140, E.091483, E.091542, E.091732, E.092020, E.092199, E.092421, E.092621, E.092820, E.092871, E.092978, E.093010, E.094755, E.095139, E.095380, E.095485, E.095627, E.096060, E.096384, E.099331, E.099715, E.099783, E.099785, E.099800, E.099821, E.099899, E.099917, E.099956, E.100023, E.100056, E.100065, E.100084, E.100142, E.100191, E.100216, E.100242, E.100271, E.100284, E.100299, E.100311, E.100348, E.100359, E.100393, E.100399, E.100401, E.100412, E.100442, E.100575, E.100577, E.100583, E.100601, E.100603, E.100612, E.100632, E.100714, E.100739, E.100796, E.100802, E.100815, E.100823, E.100836, E.100883, E.101057, E.101126, E.101152, E.101222, E.101246, E.101265, E.101365, E.101439, E.101557, E.101639, E.101654, E.101811, E.101812, E.101901, E.102030, E.102054, E.102103, E.102158, E.102174, E.102241, E.102290, E.102316, E.102362, E.102384, E.102710, E.102780, E.102904, E.103035, E.103067, E.103175, E.103194, E.103449, E.103479, E.103591, E.103599, E.103855, E.103978, E.104064, E.104067, E.104131, E.104164, E.104177, E.104228, E.104331, E.104365, E.104419, E.104442, E.104611, E.104626, E.104723, E.104760, E.104805, E.104812, E.104823, E.104824, E.105127, E.105220, E.105221, E.105281, E.105379, E.105402, E.105404, E.105409, E.105419, E.105428, E.105486, E.105514, E.105518, E.105618, E.105705, E.105723, E.105939, E.105948, E.106049, E.106078, E.106128, E.106153, E.106346, E.106392, E.106554, E.106565, E.106603, E.106633, E.107104, E.107164, E.107404, E.107485, E.107551, E.107581, E.107623, E.107798, E.107816, E.107833, E.107890, E.107897, E.107968, E.108296, E.108312, E.108375, E.108387, E.108405, E.108417, E.108465, E.108561, E.108582, E.108639, E.108641, E.108848, E.108883, E.108953, E.109062, E.109184, E.109572, E.109625, E.109758, E.109790, E.109814, E.109846, E.109956, E.110063, E.110066, E.110104, E.110107, E.110321, E.110328, E.110921, E.110955, E.111057, E.111218, E.111261, E.111335, E.111540, E.111605, E.111647, E.111785, E.111790, E.111801, E.111907, E.112039, E.112081, E.112096, E.112110, E.112144, E.112232, E.112234, E.112473, E.112578, E.112584, E.112715, E.112941, E.113013, E.113163, E.113282, E.113368, E.113441, E.113448, E.113522, E.113580, E.113645, E.113719, E.113739, E.113790, E.114054, E.114127, E.114302, E.114331, E.114388, E.114491, E.114861, E.114867, E.115053, E.115221, E.115234, E.115239, E.115241, E.115257, E.115339, E.115540, E.115541, E.115561, E.115604, E.115648, E.115738, E.115758, E.116044, E.116096, E.116127, E.116254, E.116288, E.116455, E.116478, E.116604, E.116649, E.116726, E.116754, E.116833, E.117298, E.117308, E.117335, E.117362, E.117411, E.117425, E.117448, E.117480, E.117592, E.117593, E.117614, E.117676, E.117713, E.117748, E.117751, E.117877, E.118181, E.118197, E.118260, E.118292, E.118513, E.118523, E.118640, E.118898, E.119121, E.119138, E.119318, E.119321, E.119335, E.119383, E.119421, E.119636, E.119681, E.119711, E.119820, E.119888, E.119906, E.120159, E.120328, E.120337, E.120370, E.120656, E.120733, E.120837, E.120868, E.120915, E.120948, E.121022, E.121057, E.121068, E.121104, E.121390, E.121671, E.121690, E.121749, E.121774, E.121879, E.121892, E.121903, E.121940, E.121957, E.122025, E.122033, E.122126, E.122507, E.122566, E.122705, E.122733, E.122870, E.122884, E.122952, E.123066, E.123080, E.123143, E.123154, E.123178, E.123416, E.123427, E.123595, E.123901, E.123908, E.123983, E.123992, E.124143, E.124164, E.124181, E.124193, E.124216, E.124232, E.124529, E.124562, E.124570, E.124693, E.124749, E.124767, E.124788, E.124795, E.124831, E.124942, E.125246, E.125257, E.125304, E.125352, E.125375, E.125445, E.125492, E.125676, E.125753, E.125798, E.125844, E.125868, E.125901, E.125944, E.125995, E.126062, E.126267, E.126653, E.126773, E.126777, E.126814, E.126858, E.126883, E.126934, E.126945, E.126952, E.127022, E.127328, E.127329, E.127399, E.127415, E.127554, E.127616, E.127720, E.127824, E.127884, E.127914, E.127946, E.127948, E.128050, E.128311, E.128342, E.128609, E.128626, E.128683, E.128708, E.128881, E.129315, E.129351, E.129355, E.129514, E.129636, E.129657, E.129757, E.129810, E.129990, E.130175, E.130177, E.130193, E.130255, E.130299, E.130305, E.130338, E.130340, E.130402, E.130413, E.130612, E.130713, E.130764, E.130770, E.130810, E.130826, E.130935, E.131351, E.131467, E.131473, E.131771, E.131773, E.132002, E.132275, E.132323, E.132382, E.132475, E.132481, E.132589, E.132646, E.132716, E.132881, E.133313, E.133315, E.133687, E.133835, E.133863, E.133874, E.133961, E.134077, E.134138, E.134207, E.134248, E.134308, E.134444, E.134452, E.134548, E.134684, E.134759, E.134809, E.134851, E.134955, E.135052, E.135297, E.135298, E.135387, E.135390, E.135476, E.135486, E.135525, E.135597, E.135679, E.135740, E.135829, E.135842, E.135870, E.135900, E.135914, E.135926, E.135940, E.135999, E.136044, E.136068, E.136152, E.136169, E.136280, E.136371, E.136383, E.136450, E.136521, E.136527, E.136574, E.136710, E.136750, E.136807, E.136874, E.136875, E.136930, E.136933, E.136935, E.137055, E.137124, E.137312, E.137409, E.137497, E.137513, E.137558, E.137601, E.137727, E.137776, E.137806, E.137814, E.137815, E.137948, E.137955, E.138028, E.138031, E.138041, E.138050, E.138061, E.138069, E.138073, E.138095, E.138160, E.138294, E.138347, E.138363, E.138385, E.138587, E.138594, E.138621, E.138674, E.138756, E.138757, E.138760, E.138772, E.138796, E.139211, E.139405, E.139428, E.139517, E.139613, E.139626, E.139684, E.139697, E.139874, E.140263, E.140265, E.140326, E.140350, E.140374, E.140382, E.140451, E.140481, E.140497, E.140632, E.140678, E.140694, E.140743, E.140932, E.141002, E.141012, E.141258, E.141378, E.141425, E.141429, E.141522, E.141543, E.141639, E.141744, E.141873, E.141994, E.142025, E.142208, E.142515, E.142606, E.142698, E.142765, E.142864, E.142875, E.143013, E.143294, E.143321, E.143353, E.143374, E.143375, E.143390, E.143578, E.143614, E.143621, E.143633, E.143771, E.143797, E.143816, E.143889, E.143924, E.143933, E.143947, E.144136, E.144224, E.144306, E.144381, E.144410, E.144485, E.144566, E.144671, E.144741, E.144935, E.145020, E.145632, E.145741, E.145833, E.145888, E.145907, E.145908, E.145919, E.145990, E.146067, E.146070, E.146281, E.146433, E.146457, E.146535, E.146701, E.146856, E.146966, E.147044, E.147127, E.147130, E.147133, E.147140, E.147231, E.147257, E.147403, E.147475, E.147548, E.147697, E.147724, E.148158, E.148396, E.148488, E.148672, E.148737, E.148835, E.149182, E.149218, E.149311, E.149480, E.149548, E.149646, E.150051, E.150593, E.150961, E.150991, E.151092, E.151093, E.151247, E.151304, E.151491, E.151690, E.151715, E.151726, E.151779, E.151806, E.152086, E.152207, E.152234, E.152291, E.152359, E.152377, E.152409, E.152422, E.152582, E.152763, E.152818, E.152942, E.153113, E.153140, E.153391, E.153904, E.153936, E.154099, E.154127, E.154380, E.154639, E.154723, E.154781, E.154832, E.154864, E.154889, E.154957, E.155368, E.155380, E.155508, E.155660, E.155714, E.155959, E.155980, E.156006, E.156194, E.156282, E.156304, E.156467, E.156515, E.156603, E.156650, E.156735, E.156976, E.157064, E.157103, E.157502, E.157510, E.157538, E.157551, E.157637, E.157764, E.157827, E.157992, E.158042, E.158290, E.158321, E.158485, E.158545, E.158604, E.158669, E.158715, E.158747, E.158813, E.158863, E.158901, E.158941, E.158987, E.159147, E.159184, E.159348, E.159363, E.159387, E.159423, E.159658, E.159692, E.159761, E.159921, E.160049, E.160226, E.160285, E.160294, E.160633, E.160685, E.160691, E.160789, E.160862, E.160867, E.160948, E.160972, E.161202, E.161267, E.161649, E.161692, E.161714, E.161813, E.161939, E.162069, E.162298, E.162385, E.162437, E.162490, E.162613, E.162641, E.162694, E.162910, E.162975, E.163041, E.163064, E.163110, E.163257, E.163468, E.163492, E.163530, E.163576, E.163629, E.163644, E.163749, E.163755, E.163781, E.163825, E.163913, E.163923, E.163930, E.163932, E.164045, E.164051, E.164053, E.164163, E.164244, E.164270, E.164300, E.164309, E.164442, E.164488, E.164520, E.164597, E.164749, E.164754, E.164828, E.164916, E.164919, E.164924, E.165084, E.165119, E.165138, E.165215, E.165259, E.165264, E.165280, E.165359, E.165410, E.165496, E.165637, E.165646, E.165661, E.165688, E.165695, E.165699, E.165792, E.165807, E.165813, E.165898, E.165923, E.165934, E.166263, E.166266, E.166329, E.166337, E.166341, E.166484, E.166526, E.166596, E.166598, E.166710, E.166747, E.166833, E.166860, E.166946, E.166971, E.167004, E.167085, E.167110, E.167113, E.167258, E.167513, E.167552, E.167553, E.167604, E.167635, E.167642, E.167658, E.167699, E.167744, E.167751, E.167766, E.167772, E.167799, E.167815, E.167969, E.167978, E.167987, E.167996, E.168014, E.168036, E.168066, E.168071, E.168148, E.168298, E.168393, E.168575, E.168653, E.168746, E.168763, E.168769, E.168803, E.168916, E.169087, E.169093, E.169122, E.169189, E.169213, E.169242, E.169410, E.169418, E.169562, E.169592, E.169612, E.169710, E.169763, E.169789, E.169807, E.169826, E.169957, E.170017, E.170027, E.170037, E.170088, E.170144, E.170275, E.170310, E.170315, E.170348, E.170374, E.170381, E.170396, E.170421, E.170430, E.170445, E.170549, E.170632, E.170703, E.170743, E.170837, E.170854, E.170906, E.170927, E.170954, E.170959, E.171121, E.171155, E.171180, E.171202, E.171262, E.171302, E.171345, E.171428, E.171488, E.171490, E.171492, E.171540, E.171643, E.171680, E.171723, E.171793, E.171861, E.171953, E.172115, E.172283, E.172345, E.172346, E.172466, E.172590, E.172594, E.172653, E.172717, E.172725, E.172733, E.172831, E.172867, E.172893, E.172939, E.173039, E.173230, E.173366, E.173473, E.173540, E.173585, E.173599, E.173714, E.173726, E.173805, E.173809, E.173826, E.173889, E.173898, E.173905, E.174021, E.174100, E.174332, E.174842, E.174996, E.175063, E.175110, E.175166, E.175175, E.175182, E.175198, E.175203, E.175216, E.175220, E.175334, E.175416, E.175602, E.175866, E.175946, E.176102, E.176105, E.176155, E.176171, E.176371, E.176515, E.176900, E.176971, E.176978, E.176994, E.177156, E.177239, E.177354, E.177409, E.177425, E.177459, E.177542, E.177548, E.177565, E.177595, E.177628, E.177674, E.177679, E.177694, E.177697, E.177731, E.177752, E.177951, E.178026, E.178078, E.178104, E.178163, E.178175, E.178187, E.178234, E.178381, E.178473, E.178741, E.178828, E.178950, E.179091, E.179115, E.179119, E.179348, E.179388, E.179776, E.179796, E.179869, E.179912, E.179981, E.180035, E.180198, E.180287, E.180318, E.180667, E.180869, E.180979, E.180998, E.181072, E.181163, E.181222, E.181234, E.181513, E.181523, E.181610, E.181773, E.181873, E.181885, E.181924, E.182013, E.182054, E.182217, E.182271, E.182318, E.182319, E.182512, E.182732, E.182795, E.182872, E.182890, E.182944, E.183048, E.183092, E.183098, E.183128, E.183207, E.183292, E.183431, E.183520, E.183684, E.183723, E.183785, E.183831, E.183856, E.184007, E.184047, E.184113, E.184156, E.184254, E.184363, E.184378, E.184470, E.184481, E.184508, E.184634, E.184661, E.184697, E.184708, E.184735, E.184840, E.184916, E.185043, E.185049, E.185122, E.185219, E.185359, E.185499, E.185554, E.185591, E.185619, E.185736, E.185860, E.185896, E.185945, E.185972, E.186198, E.186205, E.186376, E.186472, E.186575, E.186591, E.186660, E.186814, E.186834, E.186868, E.186889, E.187097, E.187323, E.187492, E.187634, E.187764, E.187792, E.187823, E.187837, E.187840, E.188021, E.188171, E.188186, E.188739, E.188771, E.188846, E.189060, E.189091, E.189143, E.189144, E.189221, E.189283, E.196236, E.196419, E.196436, E.196497, E.196504, E.196526, E.196591, E.196700, E.196743, E.196796, E.196812, E.196872, E.196975, E.196993, E.197081, E.197157, E.197217, E.197223, E.197299, E.197323, E.197353, E.197451, E.197479, E.197746, E.197779, E.197813, E.197837, E.197857, E.197872, E.197969, E.197976, E.198001, E.198033, E.198040, E.198087, E.198131, E.198156, E.198168, E.198205, E.198216, E.198231, E.198265, E.198366, E.198431, E.198455, E.198563, E.198586, E.198589, E.198712, E.198721, E.198732, E.198783, E.198793, E.198804, E.198807, E.198824, E.198841, E.198951, E.203301, E.203795, E.203813, E.203837, E.203879, E.203908, E.204231, E.204316, E.204389, E.204406, E.204560, E.204574 Prostate Markers E.005893 (LAMP2), E.006756 (ARSD), (Ensembl ENSG E.010539 (ZNF200), E.014257 (ACPP), E.015133 identifiers) (CCDC88C), E.018699 (TTC27), E.044115 (CTNNA1), E.048828 (FAM120A), E.051620 (HEBP2), E.056097 (ZFR), E.060339 (CCAR1), E.063241 (ISOC2), E.064489 (MEF2BNB- MEF2B), E.064886 (CHI3L2), E.066455 (GOLGA5), E.069535 (MAOB), E.072042 (RDH11), E.072071 (LPHN1), E.074047 (GLI2), E.076248 (UNG), E.076554 (TPD52), E.077147 (TM9SF3), E.077312 (SNRPA), E.081842 (PCDHA6), E.086717 (PPEF1), E.088888 (MAVS), E.088930 (XRN2), E.089902 (RCOR1), E.090612 (ZNF268), E.092199 (HNRNPC), E.095380 (NANS), E.099783 (HNRNPM), E.100191 (SLC5A4), E.100216 (TOMM22), E.100242 (SUN2), E.100284 (TOM1), E.100401 (RANGAP1), E.100412 (ACO2), E.100836 (PABPN1), E.102054 (RBBP7), E.102103 (PQBP1), E.103599 (IQCH), E.103978 (TMEM87A), E.104177 (MYEF2), E.104228 (TRIM35), E.105428 (ZNRF4), E.105518 (TMEM205), E.106603 (C7orf44; COAL), E.108405 (P2RX1), E.111057 (KRT18), E.111218 (PRMT8), E.112081 (SRSF3), E.112144 (ICK), E.113013 (HSPA9), E.113368 (LMNB1), E.115221 (ITGB6), E.116096 (SPR), E.116754 (SRSF11), E.118197 (DDX59), E.118898 (PPL), E.119121 (TRPM6), E.119711 (ALDH6A1), E.120656 (TAF12), E.121671 (CRY2), E.121774 (KHDRBS1), E.122126 (OCRL), E.122566 (HNRNPA2B1), E.123901 (GPR83), E.124562 (SNRPC), E.124788 (ATXN1), E.124795 (DEK), E.125246 (CLYBL), E.126883 (NUP214), E.127616 (SMARCA4), E.127884 (ECHS1), E.128050 (PAICS), E.129351 (ILF3), E.129757 (CDKN1C), E.130338 (TULP4), E.130612 (CYP2G1P), E.131351 (HAUS8), E.131467 (PSME3), E.133315 (MACROD1), E.134452 (FBXO18), E.134851 (TMEM165), E.135940 (COX5B), E.136169 (SETDB2), E.136807 (CDK9), E.137727 (ARHGAP20), E.138031 (ADCY3), E.138050 (THUMPD2), E.138069 (RAB1A), E.138594 (TMOD3), E.138760 (SCARB2), E.138796 (HADH), E.139613 (SMARCC2), E.139684 (ESD), E.140263 (SORD), E.140350 (ANP32A), E.140632 (GLYR1), E.142765 (SYTL1), E.143621 (ILF2), E.143933 (CALM2), E.144410 (CPO), E.147127 (RAB41), E.151304 (SRFBP1), E.151806 (GUF1), E.152207 (CYSLTR2), E.152234 (ATP5A1), E.152291 (TGOLN2), E.154723 (ATP5J), E.156467 (UQCRB), E.159387 (IRX6), E.159761 (C16orf86), E.161813 (LARP4), E.162613 (FUBP1), E.162694 (EXTL2), E.165264 (NDUFB6), E.167113 (COQ4), E.167513 (CDT1), E.167772 (ANGPTL4), E.167978 (SRRM2), E.168916 (ZNF608), E.169763 (PRYP3), E.169789 (PRY), E.169807 (PRY2), E.170017 (ALCAM), E.170144 (HNRNPA3), E.170310 (STX8), E.170954 (ZNF415), E.170959 (DCDC5), E.171302 (CANT1), E.171643 (S100Z), E.172283 (PRYP4), E.172590 (MRPL52), E.172867 (KRT2), E.173366 (TLR9), E.173599 (PC), E.177595 (PIDD), E.178473 (UCN3), E.179981 (TSHZ1), E.181163 (NPM1), E.182319 (Tyrosine-protein kinase SgK223), E.182795 (C1orf116), E.182944 (EWSR1), E.183092 (BEGAIN), E.183098 (GPC6), E.184254 (ALDH1A3), E.185619 (PCGF3), E.186889 (TMEM17), E.187837 (HIST1H1C), E.188771 (C11orf34), E.189060 (H1F0), E.196419 (XRCC6), E.196436 (NPIPL2), E.196504 (PRPF40A), E.196796, E.196993, E.197451 (HNRNPAB), E.197746 (PSAP), E.198131 (ZNF544), E.198156, E.198732 (SMOC1), E.198793 (MTOR), E.039068 (CDH1), E.173230 (GOLGB1), E.124193 (SRSF6), E.140497 (SCAMP2), E.168393 (DTYMK), E.184708 (EIF4ENIF1), E.124164 (VAPB), E.125753 (VASP), E.118260 (CREB1), E.135052 (GOLM1), E.010244 (ZNF207), E.010278 (CD9), E.047597 (XK), E.049246 (PER3), E.069849 (ATP1B3), E.072506 (HSD17B10), E.081138 (CDH7), E.099785 (MARCH2), E.104331 (IMPAD1), E.104812 (GYS1), E.120868 (APAF1), E.123908 (EIF2C2), E.125492 (BARHL1), E.127328 (RAB3IP), E.127329 (PTPRB), E.129514 (FOXA1), E.129657 (SEC14L1), E.129990 (SYT5), E.132881 (RSG1), E.136521 (NDUFB5), E.138347 (MYPN), E.141429 (GALNT1), E.144566 (RAB5A), E.151715 (TMEM45B), E.152582 (SPEF2), E.154957 (ZNF18), E.162385 (MAGOH), E.165410 (CFL2), E.168298 (HIST1H1E), E.169418 (NPR1), E.178187 (ZNF454), E.178741 (COX5A), E.179115 (FARSA), E.182732 (RGS6), E.183431 (SF3A3), E.185049 (WHSC2), E.196236 (XPNPEP3), E.197217 (ENTPD4), E.197813, E.203301, E.116833 (NR5A2), E.121057 (AKAP1), E.005471 (ABCB4), E.071859 (FAM50A), E.084234 (APLP2), E.101222 (SPEF1), E.103175 (WFDC1), E.103449 (SALL1), E.104805 (NUCB1), E.105514 (RAB3D), E.107816 (LZTS2), E.108375 (RNF43), E.109790 (KLHL5), E.112039 (FANCE), E.112715 (VEGFA), E.121690 (DEPDC7), E.125352 (RNF113A), E.134548 (C12orf39), E.136152 (COG3), E.143816 (WNT9A), E.147130 (ZMYM3), E.148396 (SEC16A), E.151092 (NGLY1), E.151779 (NBAS), E.155508 (CNOT8), E.163755 (HPS3), E.166526 (ZNF3), E.172733 (PURG), E.176371 (ZSCAN2), E.177674 (AGTRAP), E.181773 (GPR3), E.183048 (SLC25A10; MRPL12 SLC25A10), E.186376 (ZNF75D), E.187323 (DCC), E.198712 (MT-CO2), E.203908 (C6orf221; KHDC3L), E.001497 (LAS1L), E.009694 (ODZ1), E.080572 (CXorf41; PIH1D3), E.083093 (PALB2), E.089048 (ESF1), E.100065 (CARD10), E.100739 (BDKRB1), E.102904 (TSNAXIP1), E.104824 (HNRNPL), E.107404 (DVL1), E.110066 (SUV420H1), E.120328 (PCDHB12), E.121903 (ZSCAN20), E.122025 (FLT3), E.136930 (PSMB7), E.142025 (DMRTC2), E.144136 (SLC20A1), E.146535 (GNA12), E.147140 (NONO), E.153391 (INO80C), E.164919 (COX6C), E.171540 (OTP), E.177951 (BET1L), E.179796 (LRRC3B), E.197479 (PCDHB11), E.198804 (MT-CO1), E.086205 (FOLH1), E.100632 (ERH), E.100796 (SMEK1), E.104760 (FGL1), E.114302 (PRKAR2A), E.130299 (GTPBP3), E.133961 (NUMB), E.144485 (HES6), E.167085 (PHB), E.167635 (ZNF146), E.177239 (MAN1B1), E.184481 (FOXO4), E.188171 (ZNF626), E.189221 (MAOA), E.157637 (SLC38A10), E.100883 (SRP54), E.105618 (PRPF31), E.119421 (NDUFA8), E.170837 (GPR27), E.168148 (HIST3H3), E.135525 (MAP7), E.174996 (KLC2), E.018189 (RUFY3), E.183520 (UTP11L), E.173905 (GOLIM4), E.165280 (VCP), E.022976 (ZNF839), E.059691 (PET112), E.063244 (U2AF2), E.075651 (PLD1), E.089177 (KIF16B), E.089280 (FUS), E.094755 (GABRP), E.096060 (FKBP5), E.100023 (PPIL2), E.100359 (SGSM3), E.100612 (DHRS7), E.104131 (EIF3J), E.104419 (NDRG1), E.105409 (ATP1A3), E.107623 (GDF10), E.111335 (OAS2), E.113522 (RAD50), E.115053 (NCL), E.120837 (NFYB), E.122733 (KIAA1045), E.123178 (SPRYD7), E.124181 (PLCG1), E.126858 (RHOT1), E.128609 (NDUFA5), E.128683 (GAD1), E.130255 (RPL36), E.133874 (RNF122), E.135387 (CAPRIN1), E.135999 (EPC2), E.136383 (ALPK3), E.139405 (C12orf52), E.141012 (GALNS), E.143924 (EML4), E.144671 (SLC22A14), E.145741 (BTF3), E.145907 (G3BP1), E.149311 (ATM), E.153113 (CAST), E.157538 (DSCR3), E.157992 (KRTCAP3), E.158901 (WFDC8), E.165259 (HDX), E.169410 (PTPN9), E.170421 (KRT8), E.171155 (C1GALT1C1), E.172831 (CES2), E.173726 (TOMM20), E.176515, E.177565 (TBL1XR1), E.177628 (GBA), E.179091 (CYC1), E.189091 (SF3B3), E.197299 (BLM), E.197872 (FAM49A), E.198205 (ZXDA), E.198455 (ZXDB), E.082212 (ME2), E.109956 (B3GAT1), E.169710 (FASN), E.011304 (PTBP1), E.057252 (SOAT1), E.059378 (PARP12), E.082258 (CCNT2), E.087301 (TXNDC16), E.100575 (TIMM9), E.101152 (DNAJC5), E.101812 (H2BFM), E.102384 (CENPI), E.108641 (B9D1), E.119138 (KLF9), E.119820 (YIPF4), E.125995 (ROMO1), E.132323 (ILKAP), E.134809 (TIMM10), E.134955 (SLC37A2), E.135476 (ESPL1), E.136527 (TRA2B), E.137776 (SLTM), E.139211 (AMIGO2), E.139428 (MMAB), E.139874 (SSTR1), E.143321 (HDGF), E.164244 (PRRC1), E.164270 (HTR4), E.165119 (HNRNPK), E.165637 (VDAC2), E.165661 (QSOX2), E.167258 (CDK12), E.167815 (PRDX2), E.168014 (C2CD3), E.168653 (NDUFS5), E.168769 (TET2), E.169242 (EFNA1), E.175334 (BANF1), E.175416 (CLTB), E.177156 (TALDO1), E.180035 (ZNF48), E.186591 (UBE2H), E.187097 (ENTPD5), E.188739 (RBM34), E.196497 (IPO4), E.197323 (TRIM33), E.197857 (ZNF44), E.197976 (AKAP17A), E.064201 (TSPAN32), E.088992 (TESC), E.092421 (SEMA6A), E.100601 (ALKBH1), E.101557 (USP14), E.103035 (PSMD7), E.106128 (GHRHR), E.115541 (HSPE1), E.121390 (PSPC1), E.124216 (SNAI1), E.130713 (EXOSC2), E.132002 (DNAJB1), E.139697 (SBNO1), E.140481 (CCDC33), E.143013 (LMO4), E.145020 (AMT), E.145990 (GFOD1), E.146070 (PLA2G7), E.164924 (YWHAZ), E.165807 (PPP1R36), E.167751 (KLK2), E.169213 (RAB3B), E.170906 (NDUFA3), E.172725 (CORO1B), E.174332 (GLIS1), E.181924 (CHCHD8), E.183128 (CALHM3), E.204560 (DHX16), E.204574 (ABCF1), E.146701 (MDH2), E.198366 (HIST1H3A), E.081181 (ARG2), E.185896 (LAMP1), E.077514 (POLD3), E.099800 (TIMM13), E.100299 (ARSA), E.105419 (MEIS3), E.108417 (KRT37), E.113739 (STC2), E.125868 (DSTN), E.145908 (ZNF300), E.168575 (SLC20A2), E.182271 (TMIGD1), E.197223 (C1D), E.186834 (HEXIM1), E.001561 (ENPP4), E.011451 (WIZ), E.053108 (FSTL4), E.064655 (EYA2), E.065308 (TRAM2), E.075131 (TIPIN), E.081087 (OSTM1), E.092020 (PPP2R3C), E.096384 (HSP90AB1), E.100348 (TXN2), E.100577 (GSTZ1), E.100802 (C14orf93), E.101365 (IDH3B), E.101654 (RNMT), E.103067 (ESRP2), E.104064 (GABPB1), E.104823 (ECH1), E.106565 (TMEM176B), E.108561 (C1QBP), E.115257 (PCSK4), E.116127 (ALMS1), E.117411 (B4GALT2), E.119335 (SET), E.120337 (TNFSF18), E.122033 (MTIF3), E.122507 (BBS9), E.122870 (BICC1), E.130177 (CDC16), E.130193 (C8orf55; THEME), E.130413 (STK33), E.130770 (ATPIF1), E.133687 (TMTC1), E.136874 (STX17), E.137409 (MTCH1), E.139626 (ITGB7), E.141744 (PNMT), E.145888 (GLRA1), E.146067 (FAM193B), E.146433 (TMEM181), E.149480 (MTA2), E.152377 (SPOCK1), E.152763 (WDR78), E.156976 (EIF4A2), E.157827 (FMNL2), E.158485 (CD1B), E.158863 (FAM160B2), E.161202 (DVL3), E.161714 (PLCD3), E.163064 (EN1), E.163468 (CCT3), E.164309 (CMYA5), E.164916 (FOXK1), E.165215 (CLDN3), E.167658 (EEF2), E.170549 (IRX1), E.171680 (PLEKHG5), E.178234 (GALNT11), E.179869 (ABCA13), E.179912 (R3HDM2), E.180869 (C1orf180), E.180979 (LRRC57), E.182872 (RBM10), E.183207 (RUVBL2), E.184113 (CLDN5), E.185972 (CCIN), E.189144 (ZNF573), E.197353 (LYPD2), E.197779 (ZNF81), E.198807 (PAX9), E.100442 (FKBP3), E.111790 (FGER10P2), E.136044 (APPL2), E.061794 (MRPS35), E.065427 (KARS), E.068885 (IFT80), E.104164 (PLDN; BLOC1S6), E.105127 (AKAP8), E.123066 (MED13L), E.124831 (LRRFIP1), E.125304 (TM9SF2), E.126934 (MAP2K2), E.130305 (NSUN5), E.135298 (BAI3), E.135900 (MRPL44), E.136371 (MTHFS), E.136574 (GATA4), E.140326 (CDAN1), E.141378 (PTRH2), E.141543 (EIF4A3), E.150961 (SEC24D), E.155368 (DBI), E.161649 (CD300LG), E.161692 (DBF4B), E.162437 (RAVER2), E.163257 (DCAF16), E.163576 (EFHB), E.163781 (TOPBP1), E.163913 (IFT122), E.164597 (COG5), E.165359 (DDX26B), E.165646 (SLC18A2), E.169592 (INO80E), E.169957 (ZNF768), E.171492 (LRRC8D), E.171793 (CTPS; CTPS1), E.171953 (ATPAF2), E.175182 (FAM131A), E.177354 (C10orf71), E.181610 (MRPS23), E.181873 (IBA57), E.187792 (ZNF70), E.187823 (ZCCHC16), E.196872 (C2orf55; KIAA1211L), E.198168 (SVIP), E.160633 (SAFB), E.177697 (CD151), E.181072 (CHRM2), E.012779 (ALOX5), E.065054 (SLC9A3R2), E.074071 (MRPS34), E.100815 (TRIP11), E.102030 (NAA10), E.106153 (CHCHD2), E.126814 (TRMT5), E.126952 (NXF5), E.136450 (SRSF1), E.136710 (CCDC115), E.137124 (ALDH1B1), E.143353 (LYPLAL1), E.162490 (C1orf187; DRAXIN), E.167799 (NUDT8), E.171490 (RSL1D1), E.173826 (KCNH6), E.173898 (SPTBN2), E.176900 (OR51T1), E.181513 (ACBD4), E.185554 (NXF2), E.185945 (NXF2B), E.108848 (LUC7L3), E.029363 (BCLAF1), E.038002 (AGA), E.108312 (UBTF), E.166341 (DCHS1), E.054118 (THRAP3), E.135679 (MDM2), E.166860 (ZBTB39), E.183684 (THOC4; ALYREF), E.004838 (ZMYND10), E.007264 (MATK), E.020922 (MRE11A), E.041353 (RAB27B), E.052795 (FNIP2), E.075711 (DLG1), E.087087 (SRRT), E.090060 (PAPOLA), E.095139 (ARCN1), E.099715 (PCDH11Y), E.100271 (TTLL1), E.101057 (MYBL2), E.101265 (RASSF2), E.101901 (ALG13), E.102290 (PCDH11X), E.103194 (USP10), E.106554 (CHCHD3), E.107833 (NPM3), E.110063 (DCPS), E.111540 (RAB5B), E.113448 (PDE4D), E.115339 (GALNT3), E.116254 (CHD5), E.117425 (PTCH2), E.117614 (SYF2), E.118181 (RPS25), E.118292 (C1orf54), E.119318 (RAD23B), E.121022 (COPS5), E.121104 (FAM117A), E.123427 (METTL21B), E.125676 (THOC2), E.132275 (RRP8), E.137513 (NARS2), E.138028 (CGREF1), E.139517 (LNX2), E.143614 (GATAD2B), E.143889 (HNRPLL), E.145833 (DDX46), E.147403 (RPL10), E.148158 (SNX30), E.151690 (MFSD6), E.153904 (DDAH1), E.154781 (C3orf19), E.156650 (KAT6B), E.158669 (AGPAT6), E.159363 (ATP13A2), E.163530 (DPPA2), E.164749 (HNF4G), E.165496 (RPL10L), E.165688 (PMPCA), E.165792 (METTL17), E.166598 (HSP90B1), E.168036 (CTNNB1), E.168746 (C20orf62), E.170381 (SEMA3E), E.171180 (OR2M4), E.171202 (TMEM126A), E.172594 (SMPDL3A), E.172653 (C17orf66), E.173540 (GMPPB), E.173585 (CCR9), E.173809 (TDRD12), E.175166 (PSMD2), E.177694 (NAALADL2), E.178026 (FAM211B; C22orf36), E.184363 (PKP3), E.187634 (SAMD11), E.203837 (PNLIPRP3), E.169122 (FAM110B), E.197969 (VPS13A), E.136068 (FLNB), E.075856 (SART3), E.081721 (DUSP12), E.102158 (MAGT1), E.102174 (PHEX), E.102316 (MAGED2), E.104723 (TUSC3), E.105939 (ZC3HAV1), E.108883 (EFTUD2), E.110328 (GALNTL4), E.111785 (RIC8B), E.113163 (COL4A3BP), E.115604 (IL18R1), E.117362 (APH1A), E.117480 (FAAH), E.124767 (GLO1), E.126267 (COX6B1), E.130175 (PRKCSH), E.135926 (TMBIM1), E.138674 (SEC31A), E.140451 (PIF1), E.143797 (MBOAT2), E.149646 (C20orf152), E.157064 (NMNAT2), E.160294 (MCM3AP), E.165084 (C8orf34), E.166946 (CCNDBP1), E.170348 (TMED10), E.170703 (TTLL6), E.175198 (PCCA), E.180287 (PLD5), E.183292 (MIR5096), E.187492 (CDHR4), E.188846 (RPL14), E.015479 (MATR3), E.100823 (APEX1), E.090615 (GOLGA3), E.086062 (B4GALT1), E.138385 (SSB), E.140265 (ZSCAN29), E.140932 (CMTM2), E.167969 (ECI1), E.135486 (HNRNPA1), E.137497 (NUMA1), E.181523 (SGSH), E.099956 (SMARCB1), E.049883 (PTCD2), E.082556 (OPRK1), E.090674 (MCOLN1), E.107164 (FUBP3), E.108582 (CPD), E.109758 (HGFAC), E.111605 (CPSF6), E.115239 (ASB3), E.121892 (PDS5A), E.125844 (RRBP1), E.130826 (DKC1), E.132481 (TRIM47), E.135390 (ATP5G2), E.136875 (PRPF4), E.138621 (PPCDC), E.145632 (PLK2), E.150051 (MKX), E.153140 (CETN3), E.154127 (UBASH3B), E.156194 (PPEF2), E.163825 (RTP3), E.164053 (ATRIP), E.164442 (CITED2), E.168066 (SF1), E.170430 (MGMT), E.175602 (CCDC85B), E.177752 (YIPF7), E.182512 (GLRX5), E.188186 (C7orf59), E.198721 (ECI2), E.204389 (HSPA1A), E.010256 (UQCRC1), E.076043 (REXO2), E.102362 (SYTL4), E.161939 (C17orf49), E.173039 (RELA), E.014216 (CAPN1), E.054938 (CHRDL2), E.065526 (SPEN), E.070501 (POLB), E.078808 (SDF4), E.083720 (OXCT1), E.100084 (HIRA), E.101246 (ARFRP1), E.102241 (HTATSF1), E.103591 (AAGAB), E.104626 (ERI1), E.105221 (AKT2), E.105402 (NAPA), E.105705 (SUGP1), E.106346 (USP42), E.108639 (SYNGR2), E.110107 (PRPF19), E.112473 (SLC39A7), E.113282 (CLINT1), E.115234 (SNX17), E.115561 (CHMP3), E.119906 (FAM178A), E.120733 (KDM3B), E.125375 (ATP5S), E.125798 (FOXA2), E.127415 (IDUA), E.129810 (SGOL1), E.132382 (MYBBP1A), E.133313 (CNDP2), E.134077 (THUMPD3), E.134248 (HBXIP), E.135597 (REPS1), E.137814 (HAUS2), E.138041 (SMEK2), E.140382 (HMG20A), E.143578 (CREB3L4), E.144224 (UBXN4), E.144306 (SCRN3), E.144741 (SLC25A26), E.145919 (BOD1), E.146281 (PM20D2), E.152359 (POC5), E.152409 (JMY), E.154889 (MPPE1), E.157551 (KCNJ15), E.157764 (BRAF), E.158987 (RAPGEF6), E.162069 (CCDC64B), E.162910 (MRPL55), E.163749 (CCDC158), E.164045 (CDC25A), E.164300 (SERINC5), E.165898 (ISCA2), E.167987 (VPS37C), E.168763 (CNNM3), E.170374 (SP7), E.171488 (LRRC8C), E.178381 (ZFAND2A), E.180998 (GPR137C), E.182318 (ZSCAN22), E.198040 (ZNF84), E.198216 (CACNA1E), E.198265 (HELZ), E.198586 (TLK1), E.203795 (FAM24A), E.204231 (RXRB), E.123992 (DNPEP), E.184634 (MED12), E.181885 (CLDN7), E.186660 (ZFP91), E.126777 (KTN1), E.080823 (MOK), E.1018115 (CSTF2), E.124570 (SERPINB6), E.14883 (TAF5), E.158715 (SLC45A3), E.110955 (ATP5B), E.127022 (CANX), E.142208 (AKT1), E.128881 (TTBK2), E.147231 (CXorf57), E.006210 (CX3CL1), E.009830 (POMT2), E.011114 (BTBD7), E.065057 (NTHL1), E.068724 (TTC7A), E.073584 (SMARCE1), E.079785 (DDX1), E.084463 (WBP11), E.091140 (DLD), E.099821 (POLRMT), E.101126 (ADNP), E.104442 (ARMC1), E.105486 (LIG1), E.110921 (MVK), E.113441 (LNPEP), E.115758 (ODC1), E.116726 (PRAMEF12), E.119681 (LTBP2), E.136933 (RABEPK), E.137815 (RTF1), E.138095 (LRPPRC), E.138294 (MSMB), E.141873 (SLC39A3), E.142698 (C1orf94), E.143390 (RFX5), E.148488 (ST8SIA6), E.148737 (TCF7L2), E.151491 (EPS8), E.152422 (XRCC4), E.154832 (CXXC1), E.158321 (AUTS2), E.159147 (DONSON), E.160285 (LSS), E.160862 (AZGP1), E.160948 (VPS28), E.160972 (PPP1R16A), E.165934 (CPSF2), E.167604 (NFKBID), E.167766 (ZNF83), E.168803 (ADAL), E.169612 (FAM103A1), E.171262 (FAM98B), E.172893 (DHCR7), E.173889 (PHC3), E.176971 (FIBIN), E.177548 (RABEP2), E.179119 (SPTY2D1), E.184378 (ACTRT3), E.184508 (HDDC3), E.185043 (CIB1), E.186814 (ZSCAN30), E.186868 (MAPT), E.196812 (ZSCAN16), E.198563 (DDX39B), E.124529 (HIST1H4B), E.141002 (TCF25), E.174100 (MRPL45), E.109814 (UGDH), E.138756 (BMP2K), E.065457 (ADAT1), E.105948 (TTC26), E.109184 (DCUN1D4), E.125257 (ABCC4), E.126062 (TMEM115), E.142515 (KLK3), E.144381 (HSPD1), E.166710 (B2M), E.198824 (CHAMP1), E.078902 (TOLLIP), E.099331 (MYO9B), E.102710 (FAM48A), E.107485 (GATA3), E.120948 (TARDBP), E.187764 (SEMA4D), E.103855 (CD276), E.117751 (PPP1R8), E.173714 (WFIKKN2), E.172115 (CYCS), E.005882 (PDK2), E.007952 (NOX1), E.008118 (CAMK1G), E.012061 (ERCC1), E.015171 (ZMYND11), E.036257 (CUL3), E.057608 (GDI2), E.058729 (RIOK2), E.071246 (VASH1), E.073050 (XRCC1), E.073350 (LLGL2), E.079246 (XRCC5), E.085733 (CTTN), E.091542 (ALKBH5), E.091732 (ZC3HC1), E.092621 (PHGDH), E.099899 (TRMT2A), E.099917 (MED15), E.101439 (CST3), E.103479 (RBL2), E.104611 (SH2D4A), E.105281 (SLC1A5), E.106392 (C1GALT1), E.107104 (KANK1), E.107798 (LIPA), E.108296 (CWC25), E.109572 (CLCN3), E.112110 (MRPL18), E.113790 (EHHADH), E.115648 (MLPH), E.117308 (GALE), E.117335 (CD46), E.118513 (MYB), E.118640 (VAMPS), E.119321 (FKBP15), E.122705 (CLTA), E.123983 (ACSL3), E.124232 (RBPJL), E.125901 (MRPS26), E.127399 (LRRC61), E.127554 (GFER), E.128708 (HAT1), E.129355 (CDKN2D), E.130340 (SNX9), E.130935 (NOL11), E.131771 (PPP1R1B), E.133863 (TEX15), E.134207 (SYT6), E.136935 (GOLGA1), E.141425 (RPRD1A), E.143374 (TARS2), E.143771 (CNIH4), E.146966 (DENND2A), E.148672 (GLUD1), E.150593 (PDCD4), E.153936 (HS2ST1), E.154099 (DNAAF1), E.156006 (NAT2), E.156282 (CLDN17), E.158545 (ZC3H18), E.158604 (TMED4), E.158813 (EDA), E.159184 (HOXB13), E.161267 (BDH1), E.163492 (CCDC141), E.163629 (PTPN13), E.164163 (ABCE1), E.164520 (RAET1E), E.165138 (ANKS6), E.165923 (AGBL2), E.166484 (MAPK7), E.166747 (AP1G1), E.166971 (AKTIP), E.167744 (NTF4), E.168071 (CCDC88B), E.169087 (HSPBAP1), E.170396 (ZNF804A), E.170445 (HARS), E.170632 (ARMC10), E.170743 (SYT9), E.171428 (NAT1), E.172346 (CSDC2), E.173805 (HAP1), E.175175 (PPM1E), E.175203 (DCTN2), E.177542 (SLC25A22), E.177679 (SRRM3), E.178828 (RNF186), E.182013 (PNMAL1), E.182054 (IDH2), E.182890 (GLUD2), E.184156 (KCNQ3), E.184697 (CLDN6), E.184735 (DDX53), E.184840 (TMED9), E.185219 (ZNF445), E.186198 (SLC51B), E.186205 (MOSC1; MARC1), E.189143 (CLDN4), E.196700 (ZNF512B), E.196743 (GM2A), E.198087 (CD2AP), E.198951 (NAGA), E.204406 (MBD5), E.002330 (BAD), E.105404 (RABAC1), E.114127 (XRN1), E.117713 (ARID1A), E.123143 (PKN1), E.130764 (LRRC47), E.131773 (KHDRBS3), E.137806 (NDUFAF1), E.142864 (SERBP1), E.158747 (NBL1), E.175063 (UBE2C), E.178104 (PDE4DIP), E.186472 (PCLO), E.069956 (MAPK6), E.112941 (PAPD7), E.116604 (MEF2D), E.142875 (PRKACB), E.147133 (TAF1), E.157510 (AFAP1L1), E.006625 (GGCT), E.155980 (KIF5A), E.134444 (KIAA1468), E.107968 (MAP3K8), E.117592 (PRDX6), E.123154 (WDR83), E.135297 (MTO1), E.135829 (DHX9), E.149548 (CCDC15), E.152086 (TUBA3E), E.167553 (TUBA1C), E.169826 (CSGALNACT2), E.171121 (KCNMB3), E.198033 (TUBA3C), E.147724 (FAM135B), E.170854 (MINA), E.006695 (COX10), E.067369 (TP53BP1), E.089248 (ERP29), E.112096 (SOD2), E.138073 (PREB), E.146856 (AGBL3), E.159423 (ALDH4A1), E.171345 (KRT19), E.172345 (STARD5), E.111647 (UHRF1BP1L), E.117877 (CD3EAP), E.155714 (PDZD9), E.156603 (MED19), E.075886 (TUBA3D), E.167699 (GLOD4), E.121749 (TBC1D15), E.090861 (AARS), E.093010 (COMT), E.117676 (RPS6KA1), E.157502 (MUM1L1), E.159921 (GNE), E.169562 (GJB1), E.179776 (CDH5), E.071626 (DAZAP1), E.085224 (ATRX), E.116478 (HDAC1), E.117298 (ECE1), E.176171 (BNIP3), E.177425 (PAWR), E.179348 (GATA2), E.187840 (EIF4EBP1), E.033030 (ZCCHC8), E.049239 (H6PD), E.060688 (SNRNP40), E.075239 (ACAT1), E.095627 (TDRD1), E.109625 (CPZ), E.113719 (ERGIC1), E.126773 (C14orf135; PCNXL4), E.149218 (ENDOD1), E.162975 (KCNF1), E.183785 (TUBAE), E.198589 (LRBA), E.105379 (ETFB), E.011052 (NME2), E.011143 (MKS1), E.048544 (MRPS10), E.062485 (CS), E.114054 (PCCB), E.138587 (MNS1), E.155959 (VBP1), E.181222 (POLR2A), E.183723 (CMTM4), E.184661 (CDCA2), E.204316 (MRPL38), E.140694 (PARN), E.035141 (FAM136A), E.095485 (CWF19L1), E.115540 (MOB4), E.123595 (RAB9A), E.140678 (ITGAX), E.141258 (SGSM2), E.158941 (KIAA1967), , E.169189 (NSMCE1), E.198431 (TXNRD1) E.016402 (IL20RA), E.112234 (FBXL4), E.125445 (MRPS7), E.128342 (LIF), E.164051 (CCDC51), E.175866 (BAIAP2), E.102780 (DGKH), E.203813 (HIST1H3H), E.198231 (DDX42), E.030582 (GRN), E.106049 (HIBADH), E.130810 (PPAN), E.132475 (H3F3B), E.158290 (CUL4B), E.166266 (CUL5), E.026559 (KCNG1), E.059122 (FLYWCH1), E.107897 (ACBD5), E.121068 (TBX2), E.125944 (HNRNPR), E.134308 (YWHAQ), E.137558 (PI15), E.137601 (NEK1), E.147548 (WHSC1L1), E.149182 (ARFGAP2), E.159658 (KIAA0494), E.165699 (TSC1), E.170927 (PKHD1), E.186575 (NF2), E.188021 (UBQLN2), E.167552 (TUBA1A), E.003756 (RBM5), E.134138 (MEIS2), E.008196 (TFAP2B), E.079313 (REXO1), E.089127 (OAS1), E.106078 (COBL), E.113645 (WWC1), E.116288 (PARK7), E.121940 (CLCC1), E.136280 (CCM2), E.141639 (MAPK4), E.147475 (ERLIN2), E.155660 (PDIA4), E.162298 (SYVN1), E.176978 (DPP7), E.176994 (SMCR8), E.178175 (ZNF366), E.196591 (HDAC2), E.127824 (TUBA4A), E.163932 (PRKCD), E.143375 (CGN), E.076864 (RAP1GAP), E.138772 (ANXA3), E.163041 (H3F3A), E.165813 (C10orf118), E.166337 (TAF10), E.178078 (STAP2), E.184007 (PTP4A2), E.167004 (PDIA3), E.039560 (RAI14), E.119636 (C14orf45), E.140374 (ETFA), E.143633 (C1orf131), E.144935 (TRPC1), E.156735 (BAG4), E.159348 (CYB5R1), E.170275 (CRTAP), E.172717 (FAM71D), E.172939 (OXSR1), E.176105 (YES1), E.078295 (ADCY2), E.119888 (EPCAM), E.141522 (ARHGDIA), E.184047 (DIABLO), E.109062 (SLC9A3R1), E.170037 (CNTROB), E.066557 (LRRC40), E.074964 (ARHGEF10L), E.078269 (SYNJ2), E.090013 (BLVRB), E.100142 (POLR2F), E.100399 (CHADL), E.104365 (IKBKB), E.111261 (MANSC1), E.111907 (TPD52L1), E.112578 (BYSL), E.121957 (GPSM2), E.122884 (P4HA1), E.124693 (HIST1H3B), E.126653 (NSRP1), E.130402 (ACTN4), E.138757 (G3BP2), E.150991 (UBC), E.164828 (SUN1), E.175216 (CKAP5), E.176155 (CCDC57), E.177459 (C8orf47), E.183856 (IQGAP3), E.185122 (HSF1), E.122952 (ZWINT), E.151093 (OXSM), E.067704 (IARS2), E.088899 (ProSAP- interacting protein 1), E.091483 (FH), E.114388 (NPRL2), E.114861 (FOXP1), E.135914 (HTR2B), E.197837 (HIST4H4), E.127720 (C12orf26; METTL25), E.123416 (TUBA1B), E.047410 (TPR), E.117748 (RPA2), E.133835 (HSD17B4), E.067248 (DHX29), E.121879 (PIK3CA), E.132589 (FLOT2), E.136750 (GAD2), E.160789 (LMNA), E.166329, E.170088 (TMEM192), E.175946 (KLHL38), E.178163 (ZNF518B), E.182217 (HIST2H4B), E.184470 (TXNRD2), E.110321 (EIF4G2), E.171861 (RNMTL1), E.065978 (YBX1), E.115738 (ID2), E.143294 (PRCC), E.158042 (MRPL17), E.169093 (ASMTL), E.090565 (RAB11FIP3), E.185591 (SP1), E.156304 (SCAF4), E.092978 (GPATCH2), E.100056 (DGCR14), E.100583 (SAMD15), E.105723 (GSK3A), E.107551 (RASSF4), E.107581 (EIF3A), E.107890 (ANKRD26), E.110104 (CCDC86), E.112584 (FAM120B), E.113580 (NR3C1), E.114491 (UMPS), E.137312 (FLOT1), E.137955 (RABGGTB), E.141994 (DUS3L), E.147044 (CASK), E.152818 (UTRN), E.180667 (YOD1), E.184916 (JAG2), E.196526 (AFAP1), E.198783 (ZNF830), E.108465 (CDK5RAP3), E.156515 (HK1), E.036448 (MYOM2), E.061918 (GUCY1B3), E.070785 (EIF2B3), E.116044 (NFE2L2), E.128311 (TST), E.131473 (ACLY), E.132716 (DCAF8), E.138363 (ATIC), E.166596 (WDR16), E.170027 (YWHAG), E.174021 (GNG5), E.203879 (GDI1), E.160049 (DFFA), E.010810 (FYN), E.051596 (THOC3), E.006453 (BAI1-associated protein 2-like 1), E.126945 (HNRNPH2), E.165695 (AK8), E.069869 (NEDD4), E.111801 (BTN3A3), E.112232 (KHDRBS2), E.128626 (MRPS12), E.129636 (ITFG1), E.137948 (BRDT), E.147257 (GPC3), E.155380 (SLC16A1), E.159692 (CTBP1), E.166833 (NAV2), E.172466 (ZNF24), E.175110 (MRPS22), E.176102 (CSTF3), E.179388 (EGR3), E.185359 (HGS), E.198001 (IRAK4), E.100603 (SNW1), E.162641 (AKNAD1), E.069712 (KIAA1107), E.073756 (PTGS2), E.077522 (ACTN2), E.101639 (CEP192), E.106633 (GCK), E.115241 (PPM1G), E.116649 (SRM), E.120370 (GORAB), E.124143 (ARHGAP40), E.127948 (POR), E.129315 (CCNT1), E.132646 (PCNA), E.135740 (SLC9A5), E.151726 (ACSL1), E.154380 (ENAH), E.157103 (SLC6A1), E.163930 (BAP1), E.164488 (DACT2), E.164754 (RAD21), E.175220 (ARHGAP1), E.180318 (ALX1), E.181234 (TMEM132C), E.197081 (IGF2R), E.092871 (RFFL), E.163644 (PPM1K), E.171723 (GPHN), E.108953 (YWHAE), E.072110 (ACTN1), E.077097 (TOP2B), E.090889 (KIF4A), E.114331 (ACAP2), E.114867 (EIF4G1), E.117593 (DARS2), E.118523 (CTGF), E.120915 (EPHX2), E.134759 (ELP2), E.138061 (CYP1B1), E.140743 (CDR2), E.151247 (EIF4E), E.152942 (RAD17), E.160685 (ZBTB7B), E.163923 (RPL39L), E.167642 (SPINT2), E.167996 (FTH1), E.185736 (ADARB2), E.198841 (KTI12), E.185860 (C1orf110), E.160226 (C2lorf2), E.070814 (TCOF1), E.124749 (COL21A1), E.154639 (CXADR), E.065485 (PDIA5), E.023909 (GCLM), E.100714 (MTHFD1), E.108387 (SEPT4), E.160867 (FGFR4), E.134684 (YARS), E.123080 (CDKN2C), E.065548 (ZC3H15), E.116455 (WDR77), E.117448 (AKR1A1), E.100393 (EP300), E.138160 (KIF11), E.166263 (STXBP4), E.173473 (SMARCC1), E.124942 (AHNAK), E.174842 (GLMN), E.180198 (RCC1), E.185499 (MUC1), E.143947 (RPS27A), E.170315 (UBB), E.003402 (CFLAR), E.137055 (PLAA), E.142606 (MMEL1), E.147697 (GSDMC), E.163110 (PDLIM5), E.135842 (FAM129A), E.160691 (SHC1), E.197157 (SND1), E.029725 (RABEP1), E.127946 (HIP1), E.001036 (FUCA2), E.109846 (CRYAB), E.183831 (ANKRD45), E.189283 (FHIT), E.092820 (EZR), E.104067 (TJP1), E.120159 (C9ort82; CAAP1), E.154864 (PIEZO2), E.196975 (ANXA4), E.105220 (GPI), E.127914 (AKAP9), E.135870 (RC3H1), E.026508 (CD44), E.089154 (GCN1L1), E.100311 (PDGFB), E.119383 (PPP2R4), E.075624 (ACTB), E.177409 (SAMD9L), E.177731 (FLII), E.015676 (NUDCD3), E.146457 (WTAP), E.178950 (GAK), E.167110 (GOLGA2) Prostate vesicle LAMP2, ACPP, CTNNA1, HEBP2, ISOC2, HNRNPC, HNRNPM, TOMM22, TOM1, ACO2, KRT18, HSPA9, LMNB1, SPR, PPL, ALDH6A1, HNRNPA2B1, ATXN1, SMARCA4, ECHS1, PAICS, ILF3, PSME3, COX5B, RAB1A, SCARB2, HADH, ESD, SORD, ILF2, CALM2, ATP5A1, TGOLN2, ANGPTL4, ALCAM, KRT2, PC, NPM1, C1orf116, GPC6, ALDH1A3, HIST1H1C, XRCC6, HNRNPAB, PSAP, CDH1, SCAMP2, VASP, CD9, ATP1B3, HSD17B10, APAF1, EIF2C2, RAB5A, CFL2, FARSA, XPNPEP3, ENTPD4, APLP2, NUCB1, RAB3D, VEGFA, HPS3, TSNAXIP1, HNRNPL, PSMB7, GNA12, NONO, FOLH1, PRKAR2A, PHB, HIST3H3, MAP7, VCP, U2AF2, FUS, FKBP5, NDRG1, ATP1A3, NCL, RPL36, KRT8, ClGALT1C1, FASN, PTBP1, TXNDC16, DNAJC5, SLC37A2, HNRNPK, VDAC2, PRDX2, TALDO1, USP14, PSMD7, HSPE1, DNAJB1, YWHAZ, RAB3B, CORO1B, MDH2, HIST1H3A, LAMP1, STC2, DSTN, SLC20A2, ENPP4, WIZ, HSP90AB1, IDH3B, ECH1, C1 QBP, SET, TNFSF18, ITGB7, SPOCK1, EIF4A2, CCT3, CLDN3, EEF2, LRRC57, RUVBL2, CLDN5, APPL2, TM9SF2, EIF4A3, DBI, DBF4B, SVIP, CD151, ALOX5, SLC9A3R2, RAB27B, DLG1, ARCN1, CHCHD3, RAB5B, RPS25, RPL10, DDAH1, HSP90B1, CTNNB1, PSMD2, PKP3, FLNB, EFTUD2, GLO1, PRKCSH, TMBIM1, SEC31A, TMED10, RPL14, MATR3, APEX1, B4GALT1, HNRNPA1, CPD, HSPA1A, CAPN1, CHRDL2, SPEN, SDF4, NAPA, SYNGR2, CHMP3, CNDP2, CCDC64B, SERINC5, VPS37C, DNPEP, CLDN7, KTN1, SERPINB6, ATP5B, CANX, AKT1, TTBK2, DDX1, DLD, LNPEP, LTBP2, LRPPRC, EPS8, AZGP1, VPS28, DHCR7, CIB1, DDX39B, HIST1H4B, UGDH, HSPD1, B2M, TOLLIP, CD276, CYCS, CUL3, GDI2, LLGL2, XRCC5, CTTN, PHGDH, CST3, RBL2, SLC1A5, CD46, VAMP8, CLTA, ACSL3, MRPS26, SNX9, GLUD1, TMED4, PTPN13, AP1G1, SYT9, DCTN2, IDH2, GLUD2, TMED9, CLDN4, GM2A, CD2AP, MBD5, SERBP1, NBL1, PRKACB, GGCT, PRDX6, DHX9, TUBA3E, TUBA1C, TUBA3C, ERP29, SOD2, KRT19, TUBA3D, AARS, COMT, MUM1L1, CDH5, ECE1, ACAT1, ENDOD1, TUBA8, ETFB, NME2, CS, VBP1, RAB9A, TXNRD1, LIF, BAIAP2, HIST1H3H, GRN, HIBADH, H3F3B, CUL4B, HNRNPR, YWHAQ, PKHD1, TUBA1A, PARK7, ERLIN2, PDIA4, TUBA4A, PRKCD, ANXA3, H3F3A, PTP4A2, PDIA3, ETFA, CYB5R1, CRTAP, OXSR1, YES1, EPCAM, ARHGDIA, DIABLO, SLC9A3R1, BLVRB, P4HA1, HIST1H3B, ACTN4, UBC, FH, HIST4H4, TUBA1B, HSD17B4, PIK3CA, FLOT2, LMNA, TMEM192, HIST2H4B, YBX1, EIF3A, FLOT1, UTRN, HK1, ACLY, ATIC, YWHAG, GNG5, GDI1, HNRNPH2, NEDD4, BTN3A3, SLC16A1, HGS, ACTN2, SRM, PCNA, ACSL1, RAD21, ARHGAP1, IGF2R, YWHAE, ACTN1, EIF4G1, EPHX2, EIF4E, FTH1, CXADR, MTHFD1, AKR1A1, STXBP4, AHNAK, MUC1, RPS27A, UBB, PDLIM5, FAM129A, SND1, FUCA2, CRYAB, EZR, TJP1, ANXA4, GPI, AKAP9, CD44, GCN1L1, ACTB, FLII, NUDCD3 Prostate Cancer EGFR, GLUD2, ANXA3, APLP2, BclG, Cofilin vesicles 2/cfL2, DCTN-50/DCTN2, DDAH1, ESD, FARSLA, GITRL, PRKCSH, SLC20A2, Synaptogyrin 2/SYNGR2, TM9SF2, Calnexin, TOMM22, NDRG1, RPL10, RPL14, USP14, VDAC2, LLGL2, CD63, CD81, uPAR/CD87, ADAM 9, BDKRB2, CCR5, CCT2 (TCP1-beta), PSMA, PSMA1, HSPB1, VAMP8, Rab1A, B4GALT1, Aspartyl Aminopeptidase/Dnpep, ATPase Na+/K+ beta 3/ATP1B3, BDNF, ATPB, beta 2 Microglobulin, Calmodulin 2/CALM2, CD9, XRCC5/ Ku80, SMARCA4, TOM1, Cytochrome C, Hsp10/HSPE1, COX2/PTGS2, Claudin 4/ CLDN4, Cytokeratin 8, Cortactin/CTTN, DBF4B/DRF1, ECH1, ECHS1, GOLPH2, ETS1, DIP13B/ appl2, EZH2/KMT6, GSTP1, hK2/Kif2a, IQGAP1, KLK13, Lamp-2, GM2A, Hsp40/DNAJB1, HADH/HADHSC, Hsp90B, Nucleophosmin, p130/RBL2, PHGDH, RAB3B, ANXA1, PSMD7, PTBP1, Rab5a, SCARB2, Stanniocalcin 2/STC2, TGN46/ TGOLN2, TSNAXIP1, ANXA2, CD46, KLK14, IL1alpha, hnRNP C1 + C2, hnRNP A1, hnRNP A2B1, Claudin 5, CORO1B, Integrin beta 7, CD41, CD49d, CDH2, COX5b, IDH2, ME1, PhIP, ALDOA, EDNRB/EDN3, MTA1, NKX3-1, TMPRSS2, CD10, CD24, CDH1, ADAM10, B7H3, CD276, CHRDL2, SPOCK1, VEGFA, BCHE, CD151, CD166/ALCAM, CSE1L, GPC6, CXCR3, GAL3, GDF15, IGFBP-2, HGF, KLK12, ITGAL, KLK7, KLK9, MMP 2, MMP 25, MMP10, TNFRI, Notch1, PAP-same as ACPP, PTPN13/PTPL1, seprase/FAP, TNFR1, TWEAK, VEGFR2, E-Cadherin, Hsp60, CLDN3-Claudin3, KLK6, KLK8, EDIL3 (del-1), APE1, MMP 1, MMP3, nAnS, PSP94/MSP/IGBF, PSAP, RPL19, SET, TGFB, TGM2, TIMP-1, TNFRII, MDH2, PKP1, Cystatin C, Trop2/TACSTD2, CCR2/ CD192, hnRNP M1-M4, CDKN1A, CGA, Cytokeratin 18, EpoR, GGPS1, FTL (light and heavy), GM-CSF, HSP90AA1, IDH3B, MKI67/Ki67, LTBP2, KLK1, KLK4, KLK5, LDH- A, Nav1.7/SCN9A, NRP1/CD304, PIP3/BPNT1, PKP3, CgA, PRDX2, SRVN, ATPase Na+/K+ alpha 3/ATP1A3, SLC3A2/CD98, U2AF2, TLR4 (CD284), TMPRSS1, TNFα, uPA, GloI, ALIX, PKM2, FABP5, CAV1, TLR9/CD289, ANXA4, PLEKHC1/Kindlin-2, CD71/TRFR, MBD5, SPEN/RBM15, LGALS8, SLC9A3R2, ENTPD4, ANGPTL4, p97/ VCP, TBX5, PTEN, Prohibitin, LSP1, HOXB13, DDX1, AKT1, ARF6, EZR, H3F3A, CIB1, Ku70 (XRCC6), KLK11, TMBIM6, SYT9, APAF1, CLDN7, MATR3, CD90/THY1, Tollip, NOTCH4, 14-3-3 zeta/beta, ATP5A1, DLG1, GRP94, FKBP5/FKBP51, LAMP1, LGALS3BP, GDI2, HSPA1A, NCL, KLK15, Cytokeratin basic, EDN-3, AGR2, KLK10, BRG1, FUS, Histone H4, hnRNP L, Catenin Alpha 1, hnRNP K (F45)*, MMP7*, DBI*, beta catenin, CTH, CTNND2, Ataxin 1, Proteasome 20S beta 7, ADE2, EZH2, GSTP1, Lamin B1, Coatomer Subunit Delta, ERAB, Mortalin, PKM2, IGFBP-3, CTNND1/delta 1-catenin/ p120-catenin, PKA R2, NONO, Sorbitol Dehydrogenase, Aconitase 2, VASP, Lipoamide Dehydrogenase, AP1G1, GOLPH2, ALDH6A1, AZGP1, Ago2, CNDP2, Nucleobindin-1, SerpinB6, RUVBL2, Proteasome 19S 10B, SH3PX1, SPR, Destrin, MDM4, FLNB, FASN, PSME Prostate Cancer 14-3-3 zeta/beta, Aconitase 2, ADAM 9, vesicles ADAM10, ADE2, AFM, Ago2, AGR2, AKT1, ALDH1A3, ALDH6A1, ALDOA, ALIX, ANGPTL4, ANXA1, ANXA2, ANXA3, ANXA3, ANXA4, AP1G1, APAF1, APE1, APLP2, APLP2, ARF6, Aspartyl Aminopeptidase/Dnpep, Ataxin 1, ATP5A1, ATPase Na+/K+ alpha 3/ATP1A3, ATPase Na+/K+ beta 3/ATP1B3, ATPase Na+/K+ beta 3/ATP1B3, ATPB, AZGP1, B4GALT1, B7H3, BCHE, BclG, BDKRB2, BDNF, BDNF, beta 2 Microglobulin, beta catenin, BRG1, CALM2, Calmodulin 2/ CALM2, Calnexin, Calpain 1, Catenin Alpha 1, CAV1, CCR2/CD192, CCR5, CCT2 (TCP1-beta), CD10, CD151, CD166/ALCAM, CD24, CD276, CD41, CD46, CD49d, CD63, CD71/TRFR, CD81, CD9, CD9, CD90/THY1, CDH1, CDH2, CDKN1A, CGA, CgA, CHRDL2, CIB1, CIB1, Claudin 4/CLDN4, Claudin 5, CLDN3, CLDN3-Claudin3, CLDN4, CLDN7, CNDP2, Coatomer Subunit Delta, Cofilin 2/cfL2, CORO1B, Cortactin/CTTN, COX2/PTGS2, COX5b, CSE1L, CTH, CTNND1/delta 1-catenin/p120-catenin, CTNND2, CXCR3, CYCS, Cystatin C, Cytochrome C, Cytokeratin 18, Cytokeratin 8, Cytokeratin basic, DBF4B/DRF1, DBI*, DCTN-50/DCTN2, DDAH1, DDAH1, DDX1, Destrin, DIP13B/ appl2, DIP13B/ appl2, DLG1, Dnpep, E-Cadherin, ECH1, ECHS1, ECHS1, EDIL3 (del-1), EDN-3, EDNRB/EDN3, EGFR, EIF4A3, ENTPD4, EpoR, EpoR, ERAB, ESD, ESD, ETS1, ETS1, ETS-2, EZH2, EZH2/KMT6, EZR, FABP5, FARSLA, FASN, FKBP5/FKBP51, FLNB, FTL (light and heavy), FUS, GAL3, gamma-catenin, GDF15, GDI2, GGPS1, GGPS1, GITRL, GloI, GLUD2, GM2A, GM-CSF, GOLM1/GOLPH2 Mab; clone 3B10, GOLPH2, GOLPH2, GPC6, GRP94, GSTP1, GSTP1, H3F3A, HADH/HADHSC, HGF, HIST1H3A, Histone H4, hK2/Kif2a, hnRNP A1, hnRNP A2B1, hnRNP C1 + C2, hnRNP K (F45)*, hnRNP L, hnRNP M1-M4, HOXB13, Hsp10/ HSPE1, Hsp40/DNAJB1, Hsp60, HSP90AA1, Hsp90B, HSPA1A, HSPB1, IDH2, IDH3B, IDH3B, IGFBP-2, IGFBP-3, IgG1, IgG2A, IgG2B, IL1alpha, IL1alpha, Integrin beta 7, IQGAP1, ITGAL, KLHL12/C3IP1, KLK1, KLK10, KLK11, KLK12, KLK13, KLK14, KLK15, KLK4, KLK5, KLK6, KLK7, KLK8, KLK9, Ku70 (XRCC6), Lamin B1, LAMP1, Lamp-2, LDH-A, LGALS3BP, LGALS8, Lipoamide Dehydrogenase, LLGL2, LSP1, LSP1, LTBP2, MATR3, MBD5, MDH2, MDM4, MEL MKI67/Ki67, MMP 1, MMP 2, MMP 25, MMP10, MMP-14/MT1-MMP, MMP3, MMP7*, Mortalin, MTA1, nAnS, nAnS, Nav1.7/SCN9A, NCL, NDRG1, NKX3-1, NONO, Notch1, NOTCH4, NRP1/CD304, Nucleobindin-1, Nucleophosmin, p130/RBL2, p97/VCP, PAP-same as ACPP, PHGDH, PhIP, PIP3/BPNT1, PKA R2, PKM2, PKM2, PKP1, PKP3, PLEKHC1/Kindlin-2, PRDX2, PRKCSH, Prohibitin, Proteasome 19S 10B, Proteasome 20S beta 7, PSAP, PSMA, PSMA1, PSMA1, PSMD7, PSMD7, PSME3, PSP94/MSP/IGBF, PTBP1, PTEN, PTPN13/PTPL1, Rab1A, RAB3B, Rab5a, Rad51b, RPL10, RPL10, RPL14, RPL14, RPL19, RUVBL2, SCARB2, seprase/FAP, SerpinB6, SET, SH3PX1, SLC20A2, SLC3A2/CD98, SLC9A3R2, SMARCA4, Sorbitol Dehydrogenase, SPEN/RBM15, SPOCK1, SPR, SRVN, Stanniocalcin 2/STC2, STEAP1, Synaptogyrin 2/SYNGR2, Syndecan, SYNGR2, SYT9, TAF1B/ GRHL1, TBX5, TGFB, TGM2, TGN46/TGOLN2, TIMP-1, TLR3, TLR4 (CD284), TLR9/ CD289, TM9SF2, TMBIM6, TMPRSS1, TMPRSS2, TNFR1, TNFRI, TNFRII, TNFSF18/ GITRL, TNFα, TNF, Tollip, TOM1, TOMM22, Trop2/TACSTD2, TSNAXIP1, TWEAK, U2AF2, uPA, uPAR/CD87, USP14, USP14, VAMPS, VASP, VDAC2, VEGFA, VEGFR1/FLT1, VEGFR2, VPS28, XRCC5/Ku80, XRCC5/Ku80 Prostate Vesicles/ EpCAM/TROP-1, HSA, Fibrinogen, GAPDH, General Vesicles Cholesterol Oxidase, MMP7, Complement Factor D/Adipsin, E-Cadherin, Transferrin Antibody, eNOS, IgM, CD9, Apolipoprotein B (Apo B), Ep-CAM, TBG, Kallekerin 3, IgA, IgG, Annexin V, IgG, Pyruvate Carboxylase, trypsin, AFP, TNF RI/TNFRSF1A, Aptamer CAR023, Aptamer CAR024, Aptamer CAR025, Aptamer CAR026 Ribonucleoprotein GW182, Ago2, miR-let-7a, miR-16, miR-22, complexes & miR-148a, miR-451, miR-92a, CD9, CD63, vesicles CD81 Prostate Cancer PCSA, Muc2, Adam10 vesicles Prostate Cancer Alkaline Phosphatase (AP), CD63, MyoD1, vesicles Neuron Specific Enolase, MAP1B, CNPase, Prohibitin, CD45RO, Heat Shock Protein 27, Collagen II, Laminin B1/b1, Gai1, CDw75, bcl- XL, Laminin-s, Ferritin, CD21, ADP-ribosylation Factor (ARF-6) Prostate Cancer CD56/NCAM-1, Heat Shock Protein 27/hsp27, vesicles CD45RO, MAP1B, MyoD1, CD45/T200/LCA, CD3zeta, Laminin-s, bcl-XL, Rad18, Gai1, Thymidylate Synthase, Alkaline Phosphatase (AP), CD63, MMP-16/ MT3-MMP, Cyclin C, Neuron Specific Enolase, SIRP a1, Laminin B1/b1, Amyloid Beta (APP), SODD (Silencer of Death Domain), CDC37, Gab-1, E2F-2, CD6, Mast Cell Chymase, Gamma Glutamylcysteine Synthetase (GCS) Prostate Cancer EpCAM, MMP7, PCSA, BCNP, ADAM10, vesicles KLK2, SPDEF, CD81, MFGE8, IL-8 Prostate Cancer EpCAM, KLK2, PBP, SPDEF, SSX2, SSX4 vesicles Prostate Cancer ADAM-10, BCNP, CD9, EGFR, EpCam, IL1B, vesicles KLK2, MMP7, p53, PBP, PCSA, SERPINB3, SPDEF, SSX2, SSX4 Androgen Receptor GTF2F1, CTNNB1, PTEN, APPL1, GAPDH, (AR) pathway CDC37, PNRC1, AES, UXT, RAN, PA2G4, members in cMVs JUN, BAG1, UBE2I, HDAC1, COX5B, NCOR2, STUB1, HIPK3, PXN, NCOA4 EGFR1 pathway RALBP1, SH3BGRL, RBBP7, REPS1, SNRPD2, members in cMVs CEBPB, APPL1, MAP3K3, EEF1A1, GRB2, RAC1, SNCA, MAP2K3, CEBPA, CDC42, SH3KBP1, CBL, PTPN6, YWHAB, FOXO1, JAK1, KRT8, RALGDS, SMAD2, VAV1, NDUFA13, PRKCB1, MYC, JUN, RFXANK, HDAC1, HIST3H3, PEBP1, PXN, TNIP1, PKN2 TNF-alpha BCL3, SMARCE1, RPS11, CDC37, RPL6, pathway members RPL8, PAPOLA, PSMC1, CASP3, AKT2, in cMVs MAP3K7IP2, POLR2L, TRADD, SMARCA4, HIST3H3, GNB2L1, PSMD1, PEBP1, HSPB1, TNIP1, RPS13, ZFAND5, YWHAQ, COMMD1, COPS3, POLR1D, SMARCC2, MAP3K3, BIRC3, UBE2D2, HDAC2, CASP8, MCMI, PSMD7, YWHAG, NFKBIA, CAST, YWHAB, G3BP2, PSMD13, FBL, RELB, YWHAZ, SKP1, UBE2D3, PDCD2, HSP90AA1, HDAC1, KPNA2, RPL30, GTF2I, PFDN2 Colorectal cancer CD9, EGFR, NGAL, CD81, STEAP, CD24, A33, CD66E, EPHA2, Ferritin, GPR30, GPR110, MMP9, OPN, p53, TMEM211, TROP2, TGM2, TIMP, EGFR, DR3, UNC93A, MUC17, EpCAM, MUC1, MUC2, TSG101, CD63, B7H3 Colorectal cancer DR3, STEAP, epha2, TMEM211, unc93A, A33, CD24, NGAL, EpCam, MUC17, TROP2, TETS Colorectal cancer A33, AFP, ALIX, ALX4, ANCA, APC, ASCA, AURKA, AURKB, B7H3, BANK1, BCNP, BDNF, CA-19-9, CCSA-2, CCSA-3&4, CD10, CD24, CD44, CD63, CD66 CEA, CD66e CEA, CD81, CD9, CDA, C-Erb2, CRMP-2, CRP, CRTN, CXCL12, CYFRA21-1, DcR3, DLL4, DR3, EGFR, Epcam, EphA2, FASL, FRT, GAL3, GDF15, GPCR (GPR110), GPR30, GRO-1, HBD 1, HBD2, HNP1-3, IL-1B, IL8, IMP3, L1CAM, LAMN, MACC-1, MGC20553, MCP-1, M-CSF, MIC1, MIF, MMP7, MMP9, MS4A1, MUC1, MUC17, MUC2, Ncam, NGAL, NNMT, OPN, p53, PCSA, PDGFRB, PRL, PSMA, PSME3, Reg IV, SCRN1, Sept-9, SPARC, SPON2, SPR, SRVN, TFF3, TGM2, TIMP-1, TMEM211, TNF- alpha, TPA, TPS, Trail-R2, Trail-R4, TrKB, TROP2, Tsg 101, TWEAK, UNC93A, VEGFA Colorectal cancer miR 92, miR 21, miR 9, miR 491 Colorectal cancer miR-127-3p, miR-92a, miR-486-3p, miR-378 Colorectal cancer TMEM211, MUC1, CD24 and/or GPR110 (GPCR 110) Colorectal cancer hsa-miR-376c, hsa-miR-215, hsa-miR-652, hsa-miR-582-5p, hsa-miR-324-5p, hsa-miR- 1296, hsa-miR-28-5p, hsa-miR-190, hsa-miR- 590-5p, hsa-miR-202, hsa-miR-195 Colorectal cancer A26C1A, A26C1B, A2M, ACAA2, ACE, vesicle markers ACOT7, ACP1, ACTA1, ACTA2, ACTB, ACTBL2, ACTBL3, ACTC1, ACTG1, ACTG2, ACTN1, ACTN2, ACTN4, ACTR3, ADAM10, ADSL, AGR2, AGR3, AGRN, AHCY, AHNAK, AKR1B10, ALB, ALDH16A1, ALDH1A1, ALDOA, ANXA1, ANXA11, ANXA2, ANXA2P2, ANXA4, ANXA5, ANXA6, AP2A1, AP2A2, APOA1, ARF1, ARF3, ARF4, ARF5, ARF6, ARHGDIA, ARPC3, ARPC5L, ARRDC1, ARVCF, ASCC3L1, ASNS, ATP1A1, ATP1A2, ATP1A3, ATP1B1, ATP4A, ATP5A1, ATP5B, ATP5I, ATP5L, ATP5O, ATP6AP2, B2M, BAIAP2, BAIAP2L1, BRI3BP, BSG, BUB3, C1orf58, C5orf32, CAD, CALM1, CALM2, CALM3, CAND1, CANX, CAPZA1, CBR1, CBR3, CCT2, CCT3, CCT4, CCT5, CCT6A, CCT7, CCT8, CD44, CD46, CD55, CD59, CD63, CD81, CD82, CD9, CDC42, CDH1, CDH17, CEACAM5, CFL1, CFL2, CHMP1A, CHMP2A, CHMP4B, CKB, CLDN3, CLDN4, CLDN7, CLIC1, CLIC4, CLSTN1, CLTC, CLTCL1, CLU, COL12A1, COPB1, COPB2, CORO1C, COX4I1, COX5B, CRYZ, CSPG4, CSRP1, CST3, CTNNA1, CTNNB1, CTNND1, CTTN, CYFIP1, DCD, DERA, DIP2A, DIP2B, DIP2C, DMBT1, DPEP1, DPP4, DYNC1H1, EDIL3, EEF1A1, EEF1A2, EEF1AL3, EEF1G, EEF2, EFNB1, EGFR, EHD1, EHD4, EIF3EIP, EIF3I, EIF4A1, EIF4A2, ENO1, ENO2, ENO3, EPHA2, EPHA5, EPHB1, EPHB2, EPHB3, EPHB4, EPPK1, ESD, EZR, F11R, F5, F7, FAM125A, FAM125B, FAM129B, FASLG, FASN, FAT, FCGBP, FER1L3, FKBP1A, FLNA, FLNB, FLOT1, FLOT2, G6PD, GAPDH, GARS, GCN1L1, GDI2, GK, GMDS, GNA13, GNAI2, GNAI3, GNAS, GNB1, GNB2, GNB2L1, GNB3, GNB4, GNG12, GOLGA7, GPA33, GPI, GPRC5A, GSN, GSTP1, H2AFJ, HADHA, hCG_1757335, HEPH, HIST1H2AB, HIST1H2AE, HIST1H2AJ, HIST1H2AK, HIST1H4A, HIST1H4B, HIST1H4C, HIST1H4D, HIST1H4E, HIST1H4F, HIST1H4H, HIST1H4I, HIST1H4J, HIST1H4K, HIST1H4L, HIST2H2AC, HIST2H4A, HIST2H4B, HIST3H2A, HIST4H4, HLA-A, HLA-A29.1, HLA- B, HLA-C, HLA-E, HLA-H, HNRNPA2B1, HNRNPH2, HPCAL1, HRAS, HSD17B4, HSP90AA1, HSP90AA2, HSP90AA4P, HSP90AB1, HSP90AB2P, HSP90AB3P, HSP90B1, HSPA1A, HSPA1B, HSPA1L, HSPA2, HSPA4, HSPA5, HSPA6, HSPA7, HSPA8, HSPA9, H5PD1, HSPE1, HSPG2, HYOU1, IDH1, IFITM1, IFITM2, IFITM3, IGH@, IGHG1, IGHG2, IGHG3, IGHG4, IGHM, IGHV4-31, IGK@, IGKC, IGKV1-5, IGKV2-24, IGKV3- 20, IGSF3, IGSF8, IQGAP1, IQGAP2, ITGA2, ITGA3, ITGA6, ITGAV, ITGB1, ITGB4, JUP, KIAA0174, KIAA1199, KPNB1, KRAS, KRT1, KRT10, KRT13, KRT14, KRT15, KRT16, KRT17, KRT18, KRT19, KRT2, KRT20, KRT24, KRT25, KRT27, KRT28, KRT3, KRT4, KRT5, KRT6A, KRT6B, KRT6C, KRT7, KRT75, KRT76, KRT77, KRT79, KRT8, KRT9, LAMA5, LAMP1, LDHA, LDHB, LFNG, LGALS3, LGALS3BP, LGALS4, LIMA1, LIN7A, LIN7C, LOC100128936, LOC100130553, LOC100133382, LOC100133739, LOC284889, LOC388524, LOC388720, LOC442497, LOC653269, LRP4, LRPPRC, LRSAM1, LSR, LYZ, MAN1A1, MAP4K4, MARCKS, MARCKSL1, METRNL, MFGE8, MICA, MIF, MINK1, MITD1, MMPI, MOBKL1A, MSN, MTCH2, MUC13, MYADM, MYH10, MYH11, MYH14, MYH9, MYL6, MYL6B, MYO1C, MYO1D, NARS, NCALD, NCSTN, NEDD4, NEDD4L, NME1, NME2, NOTCH1, NQO1, NRAS, P4HB, PCBP1, PCNA, PCSK9, PDCD6, PDCD6IP, PDIA3, PDXK, PEBP1, PFN1, PGK1, PHB, PHB2, PKM2, PLEC1, PLEKHB2, PLSCR3, PLXNAL PLXNB2, PPIA, PPIB, PPP2R1A, PRDX1, PRDX2, PRDX3, PRDXS, PRDX6, PRKAR2A, PRKDC, PRSS23, PSMA2, PSMC6, PSMD11, PSMD3, PSME3, PTGFRN, PTPRF, PYGB, QPCT, QSOX1, RAB10, RAB11A, RAB11B, RAB13, RAB14, RAB15, RAB1A, RAB1B, RAB2A, RAB33B, RAB35, RAB43, RAB4B, RAB5A, RAB5B, RAB5C, RAB6A, RAB6B, RAB7A, RAB8A, RAB8B, RAC1, RAC3, RALA, RALB, RAN, RANP1, RAP1A, RAP1B, RAP2A, RAP2B, RAP2C, RDX, REG4, RHOA, RHOC, RHOG, ROCK2, RP11-631M21.2, RPL10A, RPL12, RPL6, RPL8, RPLP0, RPLP0-like, RPLP1, RPLP2, RPN1, RP S13, RP S14, RP Sl5A, RP S16, RP S18, RPS20, RPS21, RPS27A, RPS3, RPS4X, RPS4Y1, RPS4Y2, RPS7, RPS8, RPSA, RPSAP15, RRAS, RRAS2, RUVBL1, RUVBL2, S100A10, S100A11, S100A14, S100A16, S100A6, S100P, SDC1, SDC4, SDCBP, SDCBP2, SERINC1, SERINC5, SERPINA1, SERPINF1, SETD4, SFN, SLC12A2, SLC12A7, SLC16A1, SLC1A5, SLC25A4, SLC25A5, SLC25A6, SLC29A1, SLC2A1, SLC3A2, SLC44A1, SLC7A5, SLC9A3R1, SMPDL3B, SNAP23, SND1, SOD1, SORT1, SPTAN1, SPTBN1, SSBP1, SSR4, TACSTD1, TAGLN2, TBCA, TCEB1, TCP1, TF, TFRC, THBS1, TJP2, TKT, TMED2, TNESF10, TNIK, TNKS1BP1, TNPO3, TOLLIP, TOMM22, TPI1, TPM1, TRAP1, TSG101, TSPAN1, TSPAN14, TSPAN15, TSPAN6, TSPAN8, TSTA3, TTYH3, TUBA1A, TUBA1B, TUBA1C, TUBA3C, TUBA3D, TUBA3E, TUBA4A, TUBA4B, TUBAE, TUBB, TUBB2A, TUBB2B, TUBB2C, TUBB3, TUBB4, TUBB4Q, TUBB6, TUFM, TXN, UBA1, UBA52, UBB, UBC, UBE2N, UBE2V2, UGDH, UQCRC2, VAMP1, VAMP3, VAMPS, VCP, VIL1, VPS25, VPS28, VPS35, VPS36, VPS37B, VPS37C, WDR1, YWHAB, YWHAE, YWHAG, YWHAH, YWHAQ, YWHAZ Colorectal Cancer hsa-miR-16, hsa-miR-25, hsa-miR-125b, hsa-miR-451, hsa-miR-200c, hsa-miR-140-3p, hsa- miR-658, hsa-miR-370, hsa-miR-1296, hsa-miR-636, hsa-miR-502-5p Breast cancer miR-21, miR-155, miR-206, miR-122a, miR-210, miR-21, miR-155, miR-206, miR-122a, miR-210, let-7, miR-10b, miR-125a, miR-125b, miR-145, miR-143, miR-145, miR-1b Breast cancer GAS5 Breast cancer ER, PR, HER2, MUC1, EGFR, KRAS, B-Raf, CYP2D6, hsp70, MART-1, TRP, HER2, hsp70, MART-1, TRP, HER2, ER, PR, Class III b-tubulin, VEGFA, ETV6-NTRK3, BCA- 225, hsp70, MARTI, ER, VEGFA, Class III b-tubulin, HER2/neu (e.g., for Her2+ breast cancer), GPR30, ErbB4 (JM) isoform, MPR8, MISIIR, CD9, EphA2, EGFR, B7H3, PSM, PCSA, CD63, STEAP, CD81, ICAM1, A33, DR3, CD66e, MFG-E8, TROP-2, Mammaglobin, Hepsin, NPGP/NPFF2, PSCA, 5T4, NGAL, EpCam, neurokinin receptor-1 (NK-1 or NK-1R), NK-2, Pai-1, CD45, CD10, HER2/ERBB2, AGTR1, NPY1R, MUC1, ESA, CD133, GPR30, BCA225, CD24, CA15.3 (MUC1 secreted), CA27.29 (MUC1 secreted), NMDAR1, NMDAR2, MAGEA, CTAG1B, NY-ESO-1, SPB, SPC, NSE, PGP9.5, progesterone receptor (PR) or its isoform (PR(A) or PR(B)), P2RX7, NDUFB7, NSE, GAL3, osteopontin, CHI3L1, IC3b, mesothelin, SPA, AQPS, GPCR, hCEA-CAM, PTP IA-2, CABYR, TMEM211, ADAM28, UNC93A, MUC17, MUC2, IL10R-beta, BCMA, HVEM/TNERSF14, Trappin-2, Elafin, ST2/IL1 R4, TNFRF14, CEACAM1, TPA1, LAMP, WF, WH1000, PECAM, BSA, TNFR Breast cancer CD9, MIS Rii, ER, CD63, MUC1, HER3, STAT3, VEGFA, BCA, CA125, CD24, EPCAM, ERB B4 Breast cancer CD10, NPGP/NPFF2, HER2/ERBB2, AGTR1, NPY1R, neurokinin receptor-1 (NK-1 or NK- 1R), NK-2, MUC1, ESA, CD133, GPR30, BCA225, CD24, CA15.3 (MUC1 secreted), CA27.29 (MUC1 secreted), NMDAR1, NMDAR2, MAGEA, CTAG1B, NY-ESO-1 Breast cancer SPB, SPC, NSE, PGP9.5, CD9, P2RX7, NDUFB7, NSE, GAL3, osteopontin, CHI3L1, EGFR, B7H3, IC3b, MUC1, mesothelin, SPA, PCSA, CD63, STEAP, AQP5, CD81, DR3, PSM, GPCR, EphA2, hCEA-CAM, PTP IA-2, CABYR, TMEM211, ADAM28, UNC93A, A33, CD24, CD10, NGAL, EpCam, MUC17, TROP-2, MUC2, IL10R-beta, BCMA, HVEM/TNFRSF14, Trappin-2 Elafin, ST2/IL1 R4, TNFRF14, CEACAM1, TPA1, LAMP, WF, WH1000, PECAM, BSA, TNFR Breast cancer BRCA, MUC-1, MUC 16, CD24, ErbB4, ErbB2 (HER2), ErbB3, HSP70, Mammaglobin, PR, PR(B), VEGFA Breast cancer CD9, HSP70, Gal3, MIS, EGFR, ER, ICB3, CD63, B7H4, MUC1, DLL4, CD81, ERB3, VEGF, BCA225, BRCA, CA125, CD174, CD24, ERB2, NGAL, GPR30, CYFRA21, CD31, cMET, MUC2, ERBB4 Breast cancer CD9, EphA2, EGFR, B7H3, PSMA, PCSA, CD63, STEAP, CD81, STEAP1, ICAM1 (CD54), PSMA, A33, DR3, CD66e, MFG-8e, TMEM211, TROP-2, EGFR, Mammoglobin, Hepsin, NPGP/NPFF2, PSCA, 5T4, NGAL, NK-2, EpCam, NK-1R, PSMA, 5T4, PAI-1, CD45 Breast cancer PGP9.5, CD9, HSP70, gal3-b2c10, EGFR, iC3b, PSMA, PCSA, CD63, MUC1, DLL4, CD81, B7-H3, HER 3 (ErbB3), MART-1, PSA, VEGF A, TIMP-1, GPCR GPR110, EphA2, MMP9, mmp7, TMEM211, UNC93a, BRCA, CA125 (MUC16), Mammaglobin, CD174 (Lewis y), CD66e CEA, CD24 c.sn3, C-erbB2, CD10, NGAL, epcam, CEA (carcinoembryonic Antigen), GPR30, CYFRA21-1, OPN, MUC17, hVEGFR2, MUC2, NCAM, ASPH, ErbB4, SPB, SPC, CD9, MS4A1, EphA2, MIS RII, HER2 (ErbB2), ER, PR (B), MRP8, CD63, B7H4, TGM2, CD81, DR3, STAT 3, MACC-1, TrKB, IL 6 Unc, OPG- 13, IL6R, EZH2, SCRN1, TWEAK, SERPINB3, CDAC1, BCA-225, DR3, A33, NPGP/NPFF2, TIMP1, BDNF, FRT, Ferritin heavy chain, seprase, p53, LDH, HSP, ost, p53, CXCL12, HAP, CRP, Gro-alpha, Tsg 101, GDF15 Breast cancer CD9, HSP70, Gal3, MIS (RII), EGFR, ER, ICB3, CD63, B7H4, MUC1, CD81, ERB3, MART1, STAT3, VEGF, BCA225, BRCA, CA125, CD174, CD24, ERB2, NGAL, GPR30, CYFRA21, CD31, cMET, MUC2, ERB4, TMEM211 Breast Cancer 5T4 (trophoblast), ADAM10, AGER/RAGE, APC, APP (β-amyloid), ASPH (A-10), B7H3 (CD276), BACE1, BAI3, BRCA1, BDNF, BIRC2, C1GALT', CA125 (MUC16), Calmodulin 1, CCL2 (MCP-1), CD9, CD10, CD127 (IL7R), CD174, CD24, CD44, CD63, CD81, CEA, CRMP-2, CXCR3, CXCR4, CXCR6, CYFRA 21, derlin 1, DLL4, DPP6, E- CAD, EpCaM, EphA2 (H-77), ER(1) ESR1 α, ER(2) ESR2 β, Erb B4, Erbb2, erb3 (Erb-B3), PA2G4, FRT (FLT1), Gal3, GPR30 (G-coupled ER1), HAP1, HER3, HSP-27, HSP70, IC3b, IL8, insig, junction plakoglobin, Keratin 15, KRAS, Mammaglobin, MART1, MCT2, MFGE8, MMP9, MRP8, Muc1, MUC17, MUC2, NCAM, NG2 (CSPG4), Ngal, NHE-3, NT5E (CD73), ODC1, OPG, OPN, p53, PARK7, PCSA, PGP9.5 (PARKS), PR(B), PSA, PSMA, RAGE, STXBP4, Survivin, TFF3 (secreted), TIMP1, TIMP2, TMEM211, TRAF4 (scaffolding), TRAIL-R2 (death Receptor 5), TrkB, Tsg 101, UNC93a, VEGF A, VEGFR2, YB-1, VEGFR1, GCDPF-15 (PIP), BigH3 (TGFb1-induced protein), 5HT2B (serotonin receptor 2B), BRCA2, BACE 1, CDH1-cadherin Breast Cancer AK5.2, ATP6V1B1, CRABP1 Breast Cancer DST.3, GATA3, KRT81 Breast Cancer AK5.2, ATP6V1B1, CRABP1, DST.3, ELF5, GATA3, KRT81, LALBA, OXTR, RASL10A, SERHL, TFAP2A.1, TFAP2A.3, TFAP2C, VTCN1 Breast Cancer TRAP; Renal Cell Carcinoma; Filamin; 14.3.3, Pan; Prohibitin; c-fos; Ang-2; GSTmu; Ang- 1; FHIT; Rad51; Inhibin alpha; Cadherin-P; 14.3.3 gamma; p18INK4c; P504S; XRCC2; Caspase 5; CREB-Binding Protein; Estrogen Receptor; IL17; Claudin 2; Keratin 8; GAPDH; CD1; Keratin, LMW; Gamma Glutamylcysteine Synthetase(GCS)/Glutamate-cysteine Ligase; a-B-Crystallin; Pax-5; MMP-19; APC; IL-3; Keratin 8 (phospho-specific Ser73); TGF-beta 2; ITK; Oct-2/; DJ-1; B7-H2; Plasma Cell Marker; Rad18; Estriol; Chk1; Prolactin Receptor; Laminin Receptor; Histone H1; CD45RO; GnRH Receptor; IP10/CRG2; Actin, Muscle Specific; S100; Dystrophin; Tubulin-a; CD3zeta; CDC37; GABA a Receptor 1; MMP-7 (Matrilysin); Heregulin; Caspase 3; CD56/NCAM-1; Gastrin 1; SREBP-1 (Sterol Regulatory Element Binding Protein-1); MLH1; PGP9.5; Factor VIII Related Antigen; ADP- ribosylation Factor (ARF-6); MHC II (HLA-DR) Ia; Survivin; CD23; G-CSF; CD2; Calretinin; Neuron Specific Enolase; CD165; Calponin; CD95/Fas; Urocortin; Heat Shock Protein 27/hsp27; Topo II beta; Insulin Receptor; Keratin 5/8; sm; Actin, skeletal muscle; CA19-9; GluR1; GRIP1; CD79a mb-1; TdT; HRP; CD94; CCK-8; Thymidine Phosphorylase; CD57; Alkaline Phosphatase (AP); CD59/MACIF/MIRE/Protectin; GLUT-1; alpha-1-antitrypsin; Presenillin; Mucin 3 (MUC3); pS2; 14-3-3 beta; MMP-13 (Collagenase-3); Fli-1; mGluR5; Mast Cell Chymase; Laminin B1/b1; Neurofilament (160 kDa); CNPase; Amylin Peptide; Gai1; CD6; alpha-1-antichymotrypsin; E2F-2; MyoD1 Ductal carcinoma Laminin B1/b1; E2F-2; TdT; Apolipoprotein D; in situ (DCIS) Granulocyte; Alkaline Phosphatase (AP); Heat Shock Protein 27/hsp27; CD95/Fas; pS2; Estriol; GLUT-1; Fibronectin; CD6; CCK-8; sm; Factor VIII Related Antigen; CD57; Plasminogen; CD71/Transferrin Receptor; Keratin 5/8; Thymidine Phosphorylase; CD45/T200/LCA; Epithelial Specific Antigen; Macrophage; CD10; MyoD1; Gai1; bcl-XL; hPL; Caspase 3; Actin, skeletal muscle; IP10/CRG2; GnRH Receptor; p35nck5a; ADP-ribosylation Factor (ARF-6); Cdk4 ; alpha-1-antitrypsin; IL17; Neuron Specific Enolase; CD56/NCAM-1; Prolactin Receptor; Cdk7; CD79a mb-1; Collagen IV; CD94; Myeloid Specific Marker; Keratin 10; Pax-5; IgM (m-Heavy Chain); CD45RO; CA19-9; Mucin 2; Glucagon; Mast Cell Chymase; MLH1; CD1; CNPase; Parkin; MHC II (HLA-DR) Ia; B7-H2; Chk1; Lambda Light Chain; MHC II (HLA-DP and DR); Myogenin; MMP-7 (Matrilysin); Topo II beta; CD53; Keratin 19; Rad18; Ret Oncoprotein; MHC II (HLA-DP); E3-binding protein (ARM1); Progesterone Receptor; Keratin 8; IgG; IgA; Tubulin; Insulin Receptor Substrate-1; Keratin 15; DR3; IL-3; Keratin 10/13; Cyclin D3; MHC I (HLA25 and HLA-Aw32); Calmodulin; Neurofilament (160 kDa) Ductal carcinoma Macrophage; Fibronectin; Granulocyte; in situ (DCIS) v. Keratin 19; Cyclin D3; CD45/T200/LCA; EGFR; other Breast cancer Thrombospondin; CD81/TAPA-1; Ruv C; Plasminogen; Collagen IV; Laminin B1/b1; CD10; TdT; Filamin; bcl-XL; 14.3.3 gamma; 14.3.3, Pan; p170; Apolipoprotein D; CD71/ Transferrin Receptor; FHIT Breast cancer 5HT2B, 5T4 (trophoblast), ACO2, ACSL3, ACTN4, ADAM10, AGR2, AGR3, ALCAM, ALDH6A1, ANGPTL4, ANO9, AP1G1, APC, APEX1, APLP2, APP (_-amyloid), ARCN1, ARHGAP35, ARL3, ASAH1, ASPH (A-10), ATP1B1, ATP1B3, ATP5I, ATP5O, ATXN1, B7H3, BACE1, BAI3, BAIAP2, BCA-200, BDNF, BigH3, BIRC2, BLVRB, BRCA, BST2, C1GALT', C1GALT1C1, C20orf3, CA125, CACYBP, Calmodulin, CAPN1, CAPNS1, CCDC64B, CCL2 (MCP-1), CCT3, CD10(BD), CD127 (IL7R), CD174, CD24, CD44, CD80, CD86, CDH1, CDH5, CEA, CFL2, CHCHD3, CHMP3, CHRDL2, CIB1, CKAP4, COPA, COX5B, CRABP2, CRIP1, CRISPLD1, CRMP-2, CRTAP, CTLA4, CUL3, CXCR3, CXCR4, CXCR6, CYB5B, CYB5R1, CYCS, CYFRA 21, DBI, DDX23, DDX39B, derlin 1, DHCR7, DHX9, DLD, DLL4, DNAJBL DPP6, DSTN, eCadherin, EEF1D, EEF2, EFTUD2, EIF4A2, EIF4A3, EpCaM, EphA2, ER(1) ESR _, ER(2) ESR2 _, Erb B4, Erb2, erb3 (Erb- B3?), ERLIN2, ESD, FARSA, FASN, FEN1, FKBP5, FLNB, FOXP3, FUS, Gal3, GCDPF- 15, GCNT2, GNA12, GNG5, GNPTG, GPC6, GPD2, GPER (GPR30), GSPT1, H3F3B, H3F3C, HADH, HAP1, HER3, HIST1H1C, HIST1H2AB, HIST1H3A, HIST1H3C, HIST1H3D, HIST1H3E, HIST1H3F, HIST1H3G, HIST1H3H, HIST1H3I, HIST1H3J, HIST2H2BF, HIST2H3A, HIST2H3C, HIST2H3D, HIST3H3, HMGB1, HNRNPA2B1, HNRNPAB, HNRNPC, HNRNPD, HNRNPH2, HNRNPK, HNRNPL, HNRNPM, HNRNPU, HPS3, HSP-27, HSP70, HSP90B1, HSPA1A, HSPA2, HSPA9, HSPE1, IC3b, IDE, IDH3B, IDO1, IFI30, IL1RL2, IL7, IL8, ILF2, ILF3, IQCG, ISOC2, IST1, ITGA7, ITGB7, junction plakoglobin, Keratin 15, KRAS, KRT19, KRT2, KRT7, KRT8, KRT9, KTN1, LAMP1, LMNA, LMNB1, LNPEP, LRPPRC, LRRC57, Mammaglobin, MAN1A1, MAN1A2, MART', MATR3, MBD5, MCT2, MDH2, MFGE8, MFGE8, MGP, MMP9, MRP8, MUC1, MUC17, MUC2, MYOSB, MYOF, NAPA, NCAM, NCL, NG2 (CSPG4), Ngal, NHE-3, NME2, NONO, NPM1, NQO1, NTSE (CD73), ODC1, OPG, OPN (SC), OS9, p53, PACSIN3, PAICS, PARK7, PARVA, PC, PCNA, PCSA, PD-1, PD-L1, PD-L2, PGP9.5, PHB, PHB2, PIK3C2B, PKP3, PPL, PR(B)?, PRDX2, PRKCB, PRKCD, PRKDC, PSA, PSAP, PSMA, PSMB7, PSMD2, PSME3, PYCARD, RAB1A, RAB3D, RAB7A, RAGE, RBL2, RNPEP, RPL14, RPL27, RPL36, RPS25, RPS4X, RPS4Y1, RPS4Y2, RUVBL2, SET, SHMT2, SLAIN1, SLC39A14, SLC9A3R2, SMARCA4, SNRPD2, SNRPD3, SNX33, SNX9, SPEN, SPR, SQSTM1, SSBP1, ST3GAL1, STXBP4, SUB1, SUCLG2, Survivin, SYT9, TFF3 (secreted), TGOLN2, THBS1, TIMP1, TIMP2, TMED10, TMED4, TMED9, TMEM211, TOM1, TRAF4 (scaffolding), TRAIL-R2, TRAP1, TrkB, Tsg 101, TXNDC16, U2AF2, UEVLD, UFC1, UNC93a, USP14, VASP, VCP, VDAC1, VEGFA, VEGFR1, VEGFR2, VPS37C, WIZ, XRCC5, XRCC6, YB-1, YWHAZ Lung cancer Pgrmc1 (progesterone receptor membrane component 1)/sigma-2 receptor, STEAP, EZH2 Lung cancer Prohibitin, CD23, Amylin Peptide, HRP, Rad51, Pax-5, Oct-3/, GLUT-1, PSCA, Thrombospondin, FHIT, a-B-Crystallin, LewisA, Vacular Endothelial Growth Factor(VEGF), Hepatocyte Factor Homologue-4, Flt-4, GluR6/7, Prostate Apoptosis Response Protein-4, GluR1, Fli-1, Urocortin, S100A4, 14-3-3 beta, P504S, HDAC1, PGP9.5, DJ-1, COX2, MMP-19, Actin, skeletal muscle, Claudin 3, Cadherin-P, Collagen IX, p27Kip1, Cathepsin D, CD30 (Reed-Sternberg Cell Marker), Ubiquitin, FSH-b, TrxR2, CCK-8, Cyclin C, CD138, TGF-beta 2, Adrenocorticotrophic Hormone, PPAR-gamma, Bcl- 6, GLUT-3, IGF-I, mRANKL, Fas-ligand, Filamin, Calretinin, O ct-1, Parathyroid Hormone, Claudin 5, Claudin 4, Raf-1 (Phospho-specific), CDC14A Phosphatase, Mitochondria, APC, Gastrin 1, Ku (p80), Gai1, XPA, Maltose Binding Protein, Melanoma (gp100), Phosphotyrosine, Amyloid A, CXCR4/Fusin, Hepatic Nuclear Factor-3B, Caspase 1, HPV 16-E7, Axonal Growth Cones, Lck, Ornithine Decarboxylase, Gamma Glutamylcysteine Synthetase(GCS)/Glutamate-cysteine Ligase, ERCC1, Calmodulin, Caspase 7 (Mch 3), CD137 (4-1BB), Nitric Oxide Synthase, brain (bNOS), E2F-2, IL-10R, L-Plastin, CD18, Vimentin, CD50/ICAM-3, Superoxide Dismutase, Adenovirus Type 5 E1A, PHAS-I, Progesterone Receptor (phospho-specific)-Serine 294, MHC II (HLA-DQ), XPG, ER Ca + 2 ATPase2, Laminin-s, E3-binding protein (ARM1), CD45RO, CD1, Cdk2, MMP-10 (Stromilysin-2), sm, Surfactant Protein B (Pro), Apolipoprotein D, CD46, Keratin 8 (phospho-specific Ser73), PCNA, PLAP, CD20, Syk, LH, Keratin 19, ADP-ribosylation Factor (ARF-6), Int-2 Oncoprotein, Luciferase, AIF (Apoptosis Inducing Factor), Grb2, bcl- X, CD16, Paxillin, MHC II (HLA-DP and DR), B-Cell, p21WAF1, MHC II (HLA-DR), Tyrosinase, E2F-1, Pds1, Calponin, Notch, CD26/DPP IV, SV40 Large T Antigen, Ku (p70/p80), Perforin, XPF, SIM Ag (SIMA-4D3), Cdk1/p34cdc2, Neuron Specific Enolase, b- 2-Microglobulin, DNA Polymerase Beta, Thyroid Hormone Receptor, Human, Alkaline Phosphatase (AP), Plasma Cell Marker, Heat Shock Protein 70/hsp70, TRP75/gp75, SRF (Serum Response Factor), Laminin B1/b1, Mast Cell Chymase, Caldesmon, CEA/CD66e, CD24, Retinoid X Receptor (hRXR), CD45/ T200/LCA, Rabies Virus, Cytochrome c, DR3, bcl-XL, Fascin, CD71/Transferrin Receptor Lung Cancer miR-497 Lung Cancer Pgrmc1 Ovarian Cancer CA-125, CA 19-9, c-reactive protein, CD95(also called Fas, Fas antigen, Fas receptor, FasR, TNFRSF6, APT1 or APO-1), FAP-1, miR-200 microRNAs, EGFR, EGFRvIII, apolipoprotein AI, apolipoprotein CIII, myoglobin, tenascin C, MSH6, claudin-3, claudin-4, caveolin-1, coagulation factor III, CD9, CD36, CD37, CD53, CD63, CD81, CD136, CD147, Hsp70, Hsp90, Rab13, Desmocollin-1, EMP-2, CK7, CK20, GCDF15, CD82, Rab-5b, Annexin V, MFG-E8, HLA-DR. MiR-200 microRNAs (miR-200a, miR-200b, miR-200c), miR-141, miR-429, JNK, Jun Prostate Cancer v AQP2, BMP5, C16orf86, CXCL13, DST, normal ERCC1, GNAO1, KLHL5, MAP4K1, NELL2, PENK, PGF, POU3F1, PRSS21, SCML1, SEMG1, SMARCD3, SNAI2, TAF1C, TNNT3 Prostate Cancer v ADRB2, ARG2, C22orf32, CYorf14, EIF1AY, Breast Cancer FEV, KLK2, KLK4, LRRC26, MAOA, NLGN4Y, PNPLA7, PVRL3, SIM2, SLC30A4, SLC45A3, STX19, TRIM36, TRPM8 Prostate Cancer v ADRB2, BAIAP2L2, C19orf33, CDX1, Colorectal Cancer CEACAM6, EEF1A2, ERN2, FAM110B, FOXA2, KLK2, KLK4, LOC389816, LRRC26, MIPOL1, SLC45A3, SPDEF, TRIM31, TRIM36, ZNF613 Prostate Cancer v ASTN2, CAB39L, CRIP1, FAM110B, FEV, Lung Cancer GSTP1, KLK2, KLK4, LOC389816, LRRC26, MUC1, PNPLA7, SIM2, SLC45A3, SPDEF, TRIM36, TRPV6, ZNF613 Prostate Cancer miRs-26a + b, miR-15, miR-16, miR-195, miR-497, miR-424, miR-206, miR-342-5p, miR- 186, miR-1271, miR-600, miR-216b, miR-519 family, miR-203 Integrins ITGA1 (CD49a, VLA1), ITGA2 (CD49b, VLA2), ITGA3 (CD49c, VLA3), ITGA4 (CD49d, VLA4), ITGA5 (CD49e, VLA5), ITGA6 (CD49f, VLA6), ITGA7 (FLJ25220), ITGA8, ITGA9 (RLC), ITGA10, ITGA11 (HsT18964), ITGAD (CD11D, FLJ39841), ITGAE (CD103, HUMINAE), ITGAL (CD11a, LFA1A), ITGAM (CD11b, MAC-1), ITGAV (CD51, VNRA, MSK8), ITGAW, ITGAX (CD11c), ITGB1 (CD29, FNRB, MSK12, MDF20), ITGB2 (CD18, LFA-1, MAC-1, MFI7), ITGB3 (CD61, GP3A, GPIIIa), ITGB4 (CD104), ITGB5 (FLJ26658), ITGB6, ITGB7, ITGB8 Glycoprotein GpIa-IIa, GpIIb-IIIa, GpIIIb, GpIb, GpIX Transcription STAT3, EZH2, p53, MACC1, SPDEF, RUNX2, YB-1 factors Kinases AURKA, AURKB Disease Markers 6Ckine, Adiponectin, Adrenocorticotropic Hormone, Agouti-Related Protein, Aldose Reductase, Alpha-1-Antichymotrypsin, Alpha-1- Antitrypsin, Alpha-1-Microglobulin, Alpha- 2-Macroglobulin, Alpha-Fetoprotein, Amphiregulin, Angiogenin, Angiopoietin-2, Angiotensin-Converting Enzyme, Angiotensinogen, Annexin A1, Apolipoprotein A-I, Apolipoprotein A-II, Apolipoprotein A-IV, Apolipoprotein B, Apolipoprotein C-I, Apolipoprotein C-III, Apolipoprotein D, Apolipoprotein E, Apolipoprotein H, Apolipoprotein(a), AXL Receptor Tyrosine Kinase, B cell-activating Factor, B Lymphocyte Chemoattractant, Bcl-2-like protein 2, Beta-2-Microglobulin, Betacellulin, Bone Morphogenetic Protein 6, Brain-Derived Neurotrophic Factor, Calbindin, Calcitonin, Cancer Antigen 125, Cancer Antigen 15-3, Cancer Antigen 19-9, Cancer Antigen 72-4, Carcinoembryonic Antigen, Cathepsin D, CD 40 antigen, CD40 Ligand, CD5 Antigen-like, Cellular Fibronectin, Chemokine CC-4, Chromogranin-A, Ciliary Neurotrophic Factor, Clusterin, Collagen IV, Complement C3, Complement Factor H, Connective Tissue Growth Factor, Cortisol, C-Peptide, C-Reactive Protein, Creatine Kinase-MB, Cystatin-C, Endoglin, Endostatin, Endothelin-1, EN-RAGE, Eotaxin-1, Eotaxin-2, Eotaxin-3, Epidermal Growth Factor, Epiregulin, Epithelial cell adhesion molecule, Epithelial-Derived Neutrophil- Activating Protein 78, Erythropoietin, E-Selectin, Ezrin, Factor VII, Fas Ligand, FASLG Receptor, Fatty Acid-Binding Protein (adipocyte), Fatty Acid-Binding Protein (heart), Fatty Acid-Binding Protein (liver), Ferritin, Fetuin-A, Fibrinogen, Fibroblast Growth Factor 4, Fibroblast Growth Factor basic, Fibulin-1C, Follicle-Stimulating Hormone, Galectin-3, Gelsolin, Glucagon, Glucagon-like Peptide 1, Glucose-6-phosphate Isomerase, Glutamate- Cysteine Ligase Regulatory subunit, Glutathione S-Transferase alpha, Glutathione S- Transferase Mu 1, Granulocyte Colony-Stimulating Factor, Granulocyte-Macrophage Colony-Stimulating Factor, Growth Hormone, Growth-Regulated alpha protein, Haptoglobin, HE4, Heat Shock Protein 60, Heparin-Binding EGF-Like Growth Factor, Hepatocyte Growth Factor, Hepatocyte Growth Factor Receptor, Hepsin, Human Chorionic Gonadotropin beta, Human Epidermal Growth Factor Receptor 2, Immunoglobulin A, Immunoglobulin E, Immunoglobulin M, Insulin, Insulin-like Growth Factor I, Insulin-like Growth Factor- Binding Protein 1, Insulin-like Growth Factor- Binding Protein 2, Insulin-like Growth Factor- Binding Protein 3, Insulin-like Growth Factor Binding Protein 4, Insulin-like Growth Factor Binding Protein 5, Insulin-like Growth Factor Binding Protein 6, Intercellular Adhesion Molecule 1, Interferon gamma, Interferon gamma Induced Protein 10, Interferon-inducible T- cell alpha chemoattractant, Interleukin-1 alpha, Interleukin-1 beta, Interleukin-1 Receptor antagonist, Interleukin-2, Interleukin-2 Receptor alpha, Interleukin-3, Interleukin-4, Interleukin-5, Interleukin-6, Interleukin-6 Receptor, Interleukin-6 Receptor subunit beta, Interleukin-7, Interleukin-8, Interleukin-10, Interleukin-11, Interleukin-12 Subunit p40, Interleukin-12 Subunit p70, Interleukin-13, Interleukin-15, Interleukin-16, Interleukin-25, Kallikrein 5, Kallikrein-7, Kidney Injury Molecule-1, Lactoylglutathione lyase, Latency- Associated Peptide of Transforming Growth Factor beta 1, Lectin-Like Oxidized LDL Receptor 1, Leptin, Luteinizing Hormone, Lymphotactin, Macrophage Colony-Stimulating Factor 1, Macrophage Inflammatory Protein-1 alpha, Macrophage Inflammatory Protein-1 beta, Macrophage Inflammatory Protein-3 alpha, Macrophage inflammatory protein 3 beta, Macrophage Migration Inhibitory Factor, Macrophage-Derived Chemokine, Macrophage- Stimulating Protein, Malondialdehyde-Modified Low-Density Lipoprotein, Maspin, Matrix Metalloproteinase-1, Matrix Metalloproteinase-2, Matrix Metalloproteinase-3, Matrix Metalloproteinase-7, Matrix Metalloproteinase-9, Matrix Metalloproteinase-9, Matrix Metalloproteinase-10, Mesothelin, MHC class I chain-related protein A, Monocyte Chemotactic Protein 1, Monocyte Chemotactic Protein 2, Monocyte Chemotactic Protein 3, Monocyte Chemotactic Protein 4, Monokine Induced by Gamma Interferon, Myeloid Progenitor Inhibitory Factor 1, Myeloperoxidase, Myoglobin, Nerve Growth Factor beta, Neuronal Cell Adhesion Molecule, Neuron-Specific Enolase, Neuropilin-1, Neutrophil Gelatinase-Associated Lipocalin, NT-proBNP, Nucleoside diphosphate kinase B, Osteopontin, Osteoprotegerin, Pancreatic Polypeptide, Pepsinogen I, Peptide YY, Peroxiredoxin-4, Phosphoserine Aminotransferase, Placenta Growth Factor, Plasminogen Activator Inhibitor 1, Platelet-Derived Growth Factor BB, Pregnancy-Associated Plasma Protein A, Progesterone, Proinsulin (inc. Total or Intact), Prolactin, Prostasin, Prostate- Specific Antigen (inc. Free PSA), Prostatic Acid Phosphatase, Protein S100-A4, Protein S100-A6, Pulmonary and Activation-Regulated Chemokine, Receptor for advanced glycosylation end products, Receptor tyrosine-protein kinase erbB-3, Resistin, S100 calcium- binding protein B, Secretin, Serotransferrin, Serum Amyloid P-Component, Serum Glutamic Oxaloacetic Transaminase, Sex Hormone-Binding Globulin, Sortilin, Squamous Cell Carcinoma Antigen-1, Stem Cell Factor, Stromal cell-derived Factor-1, Superoxide Dismutase 1 (soluble), T Lymphocyte-Secreted Protein 1-309, Tamm-Horsfall Urinary Glycoprotein, T-Cell-Specific Protein RANTES, Tenascin-C, Testosterone, Tetranectin, Thrombomodulin, Thrombopoietin, Thrombospondin-1, Thyroglobulin, Thyroid-Stimulating Hormone, Thyroxine-Binding Globulin, Tissue Factor, Tissue Inhibitor of Metalloproteinases 1, Tissue type Plasminogen activator, TNF-Related Apoptosis-Inducing Ligand Receptor 3, Transforming Growth Factor alpha, Transforming Growth Factor beta-3, Transthyretin, Trefoil Factor 3, Tumor Necrosis Factor alpha, Tumor Necrosis Factor beta, Tumor Necrosis Factor Receptor I, Tumor necrosis Factor Receptor 2, Tyrosine kinase with Ig and EGF homology domains 2, Urokinase-type Plasminogen Activator, Urokinase-type plasminogen activator Receptor, Vascular Cell Adhesion Molecule-1, Vascular Endothelial Growth Factor, Vascular endothelial growth Factor B, Vascular Endothelial Growth Factor C, Vascular endothelial growth Factor D, Vascular Endothelial Growth Factor Receptor 1, Vascular Endothelial Growth Factor Receptor 2, Vascular endothelial growth Factor Receptor 3, Vitamin K-Dependent Protein S, Vitronectin, von Willebrand Factor, YKL-40 Disease Markers Adiponectin, Adrenocorticotropic Hormone, Agouti-Related Protein, Alpha-1- Antichymotrypsin, Alpha-l-Antitrypsin, Alpha-l-Microglobulin, Alpha-2-Macroglobulin, Alpha-Fetoprotein, Amphiregulin, Angiopoietin-2, Angiotensin-Converting Enzyme, Angiotensinogen, Apolipoprotein A-I, Apolipoprotein A-II, Apolipoprotein A-IV, Apolipoprotein B, Apolipoprotein C-I, Apolipoprotein C-III, Apolipoprotein D, Apolipoprotein E, Apolipoprotein H, Apolipoprotein(a), AXL Receptor Tyrosine Kinase, B Lymphocyte Chemoattractant, Beta-2- Microglobulin, Betacellulin, Bone Morphogenetic Protein 6, Brain-Derived Neurotrophic Factor, Calbindin, Calcitonin, Cancer Antigen 125, Cancer Antigen 19-9, Carcinoembryonic Antigen, CD 40 antigen, CD40 Ligand, CD5 Antigen-like, Chemokine CC-4, Chromogranin-A, Ciliary Neurotrophic Factor, Clusterin, Complement C3, Complement Factor H, Connective Tissue Growth Factor, Cortisol, C- Peptide, C-Reactive Protein, Creatine Kinase-MB, Cystatin-C, Endothelin-1, EN-RAGE, Eotaxin-1, Eotaxin-3, Epidermal Growth Factor, Epiregulin, Epithelial-Derived Neutrophil- Activating Protein 78, Erythropoietin, E-Selectin, Factor VII, Fas Ligand, FASLG Receptor, Fatty Acid-Binding Protein (heart), Ferritin, Fetuin-A, Fibrinogen, Fibroblast Growth Factor 4, Fibroblast Growth Factor basic, Follicle- Stimulating Hormone, Glucagon, Glucagon-like Peptide 1, Glutathione S-Transferase alpha, Granulocyte Colony-Stimulating Factor, Granulocyte-Macrophage Colony-Stimulating Factor, Growth Hormone, Growth-Regulated alpha protein, Haptoglobin, Heat Shock Protein 60, Heparin-Binding EGF-Like Growth Factor, Hepatocyte Growth Factor, Immunoglobulin A, Immunoglobulin E, Immunoglobulin M, Insulin, Insulin-like Growth Factor I, Insulin-like Growth Factor-Binding Protein 2, Intercellular Adhesion Molecule 1, Interferon gamma, Interferon gamma Induced Protein 10, Interleukin-1 alpha, Interleukin-1 beta, Interleukin-1 Receptor antagonist, Interleukin-2, Interleukin-3, Interleukin-4, Interleukin-5, Interleukin-6, Interleukin-6 Receptor, Interleukin- 7, Interleukin-8, Interleukin-10, Interleukin-11, Interleukin-12 Subunit p40, Interleukin-12 Subunit p70, Interleukin-13, Interleukin-15, Interleukin-16, Interleukin-25, Kidney Injury Molecule-1, Lectin-Like Oxidized LDL Receptor 1, Leptin, Luteinizing Hormone, Lymphotactin, Macrophage Colony-Stimulating Factor 1, Macrophage Inflammatory Protein- 1 alpha, Macrophage Inflammatory Protein-1 beta, Macrophage Inflammatory Protein-3 alpha, Macrophage Migration Inhibitory Factor, Macrophage-Derived Chemokine, Malondialdehyde-Modified Low-Density Lipoprotein, Matrix Metalloproteinase-1, Matrix Metalloproteinase-2, Matrix Metalloproteinase-3, Matrix Metalloproteinase-7, Matrix Metalloproteinase-9, Matrix Metalloproteinase-9, Matrix Metalloproteinase-10, Monocyte Chemotactic Protein 1, Monocyte Chemotactic Protein 2, Monocyte Chemotactic Protein 3, Monocyte Chemotactic Protein 4, Monokine Induced by Gamma Interferon, Myeloid Progenitor Inhibitory Factor 1, Myeloperoxidase, Myoglobin, Nerve Growth Factor beta, Neuronal Cell Adhesion Molecule, Neutrophil Gelatinase-Associated Lipocalin, NT-proBNP, Osteopontin, Pancreatic Polypeptide, Peptide YY, Placenta Growth Factor, Plasminogen Activator Inhibitor 1, Platelet-Derived Growth Factor BB, Pregnancy-Associated Plasma Protein A, Progesterone, Proinsulin (inc. Intact or Total), Prolactin, Prostate-Specific Antigen (inc. Free PSA), Prostatic Acid Phosphatase, Pulmonary and Activation-Regulated Chemokine, Receptor for advanced glycosylation end products, Resistin, S100 calcium- binding protein B, Secretin, Serotransferrin, Serum Amyloid P-Component, Serum Glutamic Oxaloacetic Transaminase, Sex Hormone- Binding Globulin, Sortilin, Stem Cell Factor, Superoxide Dismutase 1 (soluble), T Lymphocyte- Secreted Protein I-309, Tamm-Horsfall Urinary Glycoprotein, T-Cell-Specific Protein RANTES, Tenascin-C, Testosterone, Thrombomodulin, Thrombopoietin, Thrombospondin-1, Thyroid-Stimulating Hormone, Thyroxine-Binding Globulin, Tissue Factor, Tissue Inhibitor of Metalloproteinases 1, TNF- Related Apoptosis-Inducing Ligand Receptor 3, Transforming Growth Factor alpha, Transforming Growth Factor beta-3, Transthyretin, Trefoil Factor 3, Tumor Necrosis Factor alpha, Tumor Necrosis Factor beta, Tumor l necrosis Factor Receptor 2, Vascular Cel Adhesion Molecule-1, Vascular Endothelial Growth Factor, Vitamin K-Dependent Protein S, Vitronectin, von Willebrand Factor Oncology 6Ckine, Aldose Reductase, Alpha-Fetoprotein, Amphiregulin, Angiogenin, Annexin A1, B cell-activating Factor, B Lymphocyte Chemoattractant, Bcl-2-like protein 2, Betacellulin, Cancer Antigen 125, Cancer Antigen 15-3, Cancer Antigen 19-9, Cancer Antigen 72-4, Carcinoembryonic Antigen, Cathepsin D, Cellular Fibronectin, Collagen IV, Endoglin, Endostatin, Eotaxin-2, Epidermal Growth Factor, Epiregulin, Epithelial cell adhesion molecule, Ezrin, Fatty Acid-Binding Protein (adipocyte), Fatty Acid-Binding Protein (liver), Fibroblast Growth Factor basic, Fibulin-1C, Galectin-3, Gelsolin, Glucose-6-phosphate Isomerase, Glutamate-Cysteine Ligase Regulatory subunit, Glutathione S-Transferase Mu 1, HE4, Heparin-Binding EGF-Like Growth Factor, Hepatocyte Growth Factor, Hepatocyte Growth Factor Receptor, Hepsin, Human Chorionic Gonadotropin beta, Human Epidermal Growth Factor Receptor 2, Insulin-like Growth Factor-Binding Protein 1, Insulin-like Growth Factor-Binding Protein 2, Insulin-like Growth Factor-Binding Protein 3, Insulin-like Growth Factor Binding Protein 4, Insulin-like Growth Factor Binding Protein 5, Insulin-like Growth Factor Binding Protein 6, Interferon gamma Induced Protein 10, Interferon-inducible T-cell alpha chemoattractant, Interleukin-2 Receptor alpha, Interleukin-6, Interleukin-6 Receptor subunit beta, Kallikrein 5, Kallikrein-7, Lactoylglutathione lyase, Latency-Associated Peptide of Transforming Growth Factor beta 1, Leptin, Macrophage inflammatory protein 3 beta, Macrophage Migration Inhibitory Factor, Macrophage-Stimulating Protein, Maspin, Matrix Metalloproteinase-2, Mesothelin, MHC class I chain-related protein A, Monocyte Chemotactic Protein 1, Monokine Induced by Gamma Interferon, Neuron-Specific Enolase, Neuropilin-1, Neutrophil Gelatinase-Associated Lipocalin, Nucleoside diphosphate kinase B, Osteopontin, Osteoprotegerin, Pepsinogen I, Peroxiredoxin-4, Phosphoserine Aminotransferase, Placenta Growth Factor, Platelet-Derived Growth Factor BB, Prostasin, Protein S100-A4, Protein S100-A6, Receptor tyrosine-protein kinase erbB-3, Squamous Cell Carcinoma Antigen-1, Stromal cell-derived Factor-1, Tenascin-C, Tetranectin, Thyroglobulin, Tissue type Plasminogen activator, Transforming Growth Factor alpha, Tumor Necrosis Factor Receptor I, Tyrosine kinase with Ig and EGF homology domains 2, Urokinase-type Plasminogen Activator, Urokinase-type plasminogen activator Receptor, Vascular Endothelial Growth Factor, Vascular endothelial growth Factor B, Vascular Endothelial Growth Factor C, Vascular endothelial growth Factor D, Vascular Endothelial Growth Factor Receptor 1, Vascular Endothelial Growth Factor Receptor 2, Vascular endothelial growth Factor Receptor 3, YKL-40 Disease Adiponectin, Alpha-1-Antitrypsin, Alpha-2-Macroglobulin, Alpha-Fetoprotein, Apolipoprotein A-I, Apolipoprotein C-III, Apolipoprotein H, Apolipoprotein(a), Beta-2- Microglobulin, Brain-Derived Neurotrophic Factor, Calcitonin, Cancer Antigen 125, Cancer Antigen 19-9, Carcinoembryonic Antigen, CD 40 antigen, CD40 Ligand, Complement C3, C- Reactive Protein, Creatine Kinase-MB, Endothelin-1, EN-RAGE, Eotaxin-1, Epidermal Growth Factor, Epithelial-Derived Neutrophil- Activating Protein 78, Erythropoietin, Factor VII, Fatty Acid-Binding Protein (heart), Ferritin, Fibrinogen, Fibroblast Growth Factor basic, Granulocyte Colony-Stimulating Factor, Granulocyte-Macrophage Colony-Stimulating Factor, Growth Hormone, Haptoglobin, Immunoglobulin A, Immunoglobulin E, Immunoglobulin M, Insulin, Insulin-like Growth Factor I, Intercellular Adhesion Molecule 1, Interferon gamma, Interleukin-1 alpha, Interleukin-1 beta, Interleukin-1 Receptor antagonist, Interleukin-2, Interleukin-3, Interleukin-4, Interleukin-5, Interleukin-6, Interleukin-7, Interleukin-8, Interleukin-10, Interleukin-12 Subunit p40, Interleukin-12 Subunit p70, Interleukin-13, Interleukin-15, Interleukin-16, Leptin, Lymphotactin, Macrophage Inflammatory Protein-1 alpha, Macrophage Inflammatory Protein-1 beta, Macrophage- Derived Chemokine, Matrix Metalloproteinase-2, x Matrix Metalloproteinase-3, Matri Metalloproteinase-9, Monocyte Chemotactic Protein 1, Myeloperoxidase, Myoglobin, Plasminogen Activator Inhibitor 1, Pregnancy- Associated Plasma Protein A, Prostate- Specific Antigen (inc. Free PSA), Prostatic Acid Phosphatase, Serum Amyloid P-Component, Serum Glutamic Oxaloacetic Transaminase, Sex Hormone-Binding Globulin, Stem Cell Factor, T-Cell-Specific Protein RANTES, Thrombopoietin, Thyroid-Stimulating Hormone, Thyroxine-Binding Globulin, Tissue Factor, Tissue Inhibitor of Metalloproteinases 1, Tumor Necrosis Factor alpha, Tumor Necrosis Factor beta, Tumor Necrosis Factor Receptor 2, Vascular Cell Adhesion Molecule-1, Vascular Endothelial Growth Factor, von Willebrand Factor Neurological Alpha-1-Antitrypsin, Apolipoprotein A-I, Apolipoprotein A-II, Apolipoprotein B, Apolipoprotein C-I, Apolipoprotein H, Beta-2- Microglobulin, Betacellulin, Brain-Derived Neurotrophic Factor, Calbindin, Cancer Antigen 125, Carcinoembryonic Antigen, CD5 Antigen-like, Complement C3, Connective Tissue Growth Factor, Cortisol, Endothelin-1, Epidermal Growth Factor Receptor, Ferritin, Fetuin-A, Follicle-Stimulating Hormone, Haptoglobin, Immunoglobulin A, Immunoglobulin M, Intercellular Adhesion Molecule 1, Interleukin-6 Receptor, Interleukin-7, Interleukin-10, Interleukin-11, Interleukin-17, Kidney Injury Molecule-1, Luteinizing Hormone, Macrophage-Derived Chemokine, Macrophage Migration Inhibitory Factor, Macrophage Inflammatory Protein-1 alpha, Matrix Metalloproteinase-2, Monocyte Chemotactic Protein 2, Peptide YY, Prolactin, Prostatic Acid Phosphatase, Serotransferrin, Serum Amyloid P-Component, Sortilin, Testosterone, Thrombopoietin, Thyroid-Stimulating Hormone, Tissue Inhibitor of Metalloproteinases 1, TNF-Related Apoptosis-Inducing Ligand Receptor 3, Tumor necrosis Factor Receptor 2, Vascular Endothelial Growth Factor, Vitronectin Cardiovascular Adiponectin, Apolipoprotein A-I, Apolipoprotein , B, Apolipoprotein C-III, Apolipoprotein D Apolipoprotein E, Apolipoprotein H, Apolipoprotein(a), Clusterin, C-Reactive Protein, Cystatin-C, EN-RAGE, E-Selectin, Fatty Acid-Binding Protein (heart), Ferritin, Fibrinogen, Haptoglobin, Immunoglobulin M, Intercellular Adhesion Molecule 1, Interleukin-6, Interleukin-8, Lectin-Like Oxidized LDL Receptor 1, Leptin, Macrophage Inflammatory Protein-1 alpha, Macrophage Inflammatory Protein-1 beta, Malondialdehyde-Modified Low- Density Lipoprotein, Matrix Metalloproteinase-1, Matrix Metalloproteinase-10, Matrix Metalloproteinase-2, Matrix Metalloproteinase-3, Matrix Metalloproteinase-7, Matrix Metalloproteinase-9, Monocyte Chemotactic Protein 1, Myeloperoxidase, Myoglobin, NT- proBNP, Osteopontin, Plasminogen Activator Inhibitor 1, P-Selectin, Receptor for advanced glycosylation end products, Serum Amyloid P-Component, Sex Hormone-Binding Globulin, T-Cell-Specific Protein RANTES, Thrombomodulin, Thyroxine-Binding Globulin, Tissue Inhibitor of Metalloproteinases 1, Tumor Necrosis Factor alpha, Tumor necrosis Factor Receptor 2, Vascular Cell Adhesion Molecule-1, von Willebrand Factor Inflammatory Alpha-1-Antitrypsin, Alpha-2-Macroglobulin, Beta-2-Microglobulin, Brain-Derived Neurotrophic Factor, Complement C3, C-Reactive Protein, Eotaxin-1, Factor VII, Ferritin, Fibrinogen, Granulocyte-Macrophage Colony-Stimulating Factor, Haptoglobin, Intercellular Adhesion Molecule 1, Interferon gamma, Interleukin-1 alpha, Interleukin-1 beta, Interleukin- 1 Receptor antagonist, Interleukin-2, Interleukin-3, Interleukin-4, Interleukin-5, Interleukin-6, Interleukin-7, Interleukin-8, Interleukin-10, Interleukin-12 Subunit p40, Interleukin-12 Subunit p70, Interleukin-15, Interleukin-17, Interleukin-23, Macrophage Inflammatory Protein-1 alpha, Macrophage Inflammatory Protein-1 beta, Matrix Metalloproteinase-2, Matrix Metalloproteinase-3, Matrix Metalloproteinase-9, Monocyte Chemotactic Protein 1, Stem Cell Factor, T-Cell-Specific Protein RANTES, Tissue Inhibitor of Metalloproteinases 1, Tumor Necrosis Factor alpha, Tumor Necrosis Factor beta, Tumor necrosis Factor Receptor 2, Vascular Cell Adhesion Molecule-1, Vascular Endothelial Growth Factor, Vitamin D- Binding Protein, von Willebrand Factor Metabolic Adiponectin, Adrenocorticotropic Hormone, Angiotensin-Converting Enzyme, Angiotensinogen, Complement C3 alpha des arg, Cortisol, Follicle-Stimulating Hormone, Galanin, Glucagon, Glucagon-like Peptide 1, Insulin, Insulin-like Growth Factor I, Leptin, Luteinizing Hormone, Pancreatic Polypeptide, Peptide YY, Progesterone, Prolactin, Resistin, Secretin, Testosterone Kidney Alpha-1-Microglobulin, Beta-2-Microglobulin, Calbindin, Clusterin, Connective Tissue Growth Factor, Creatinine, Cystatin-C, Glutathione S-Transferase alpha, Kidney Injury Molecule-1, Microalbumin, Neutrophil Gelatinase-Associated Lipocalin, Osteopontin, Tamm-Horsfall Urinary Glycoprotein, Tissue Inhibitor of Metalloproteinases 1, Trefoil Factor 3, Vascular Endothelial Growth Factor Cytokines Granulocyte-Macrophage Colony-Stimulating Factor, Interferon gamma, Interleukin-2, Interleukin-3, Interleukin-4, Interleukin-5, Interleukin-6, Interleukin-7, Interleukin-8, Interleukin-10, Macrophage Inflammatory Protein-1 alpha, Macrophage Inflammatory Protein-1 beta, Matrix Metalloproteinase-2, Monocyte Chemotactic Protein 1, Tumor Necrosis Factor alpha, Tumor Necrosis Factor beta, Brain-Derived Neurotrophic Factor, Eotaxin-1, Intercellular Adhesion Molecule 1, Interleukin-1 alpha, Interleukin-1 beta, Interleukin-1 Receptor antagonist, Interleukin-12 Subunit p40, Interleukin-12 Subunit p70, Interleukin-15, Interleukin-17, Interleukin-23, Matrix Metalloproteinase-3, Stem Cell Factor, Vascular Endothelial Growth Factor Protein 14.3.3 gamma, 14.3.3 (Pan), 14-3-3 beta, 6-Histidine, a-B-Crystallin, Acinus, Actin beta, Actin (Muscle Specific), Actin (Pan), Actin (skeletal muscle), Activin Receptor Type II, Adenovirus, Adenovirus Fiber, Adenovirus Type 2 E1A, Adenovirus Type 5 E1A, ADP- ribosylation Factor (ARF-6), Adrenocorticotrophic Hormone, AIF (Apoptosis Inducing Factor), Alkaline Phosphatase (AP), Alpha Fetoprotein (AFP), Alpha Lactalbumin, alpha-1- antichymotrypsin, alpha-1-antitrypsin, Amphiregulin, Amylin Peptide, Amyloid A, Amyloid A4 Protein Precursor, Amyloid Beta (APP), Androgen Receptor, Ang-1, Ang-2, APC, APC11, APC2, Apolipoprotein D, A-Raf, ARC, Ask1/MAPKKK5, ATM, Axonal Growth Cones, b Galactosidase, b-2-Microglobulin, B7-H2, BAG-1, Bak, Bax, B-Cell, B-cell Linker Protein (BLNK), Bcl10/CIPER/CLAP/mE10, bcl-2a, Bcl-6, bcl-X, bcl-XL, Bim (BOD), Biotin, Bonzo/STRL33/TYMSTR, Bovine Serum Albumin, BRCA2 (aa 1323-1346), BrdU, Bromodeoxyuridine (BrdU), CA125, CA19-9, c-Abl, Cadherin (Pan), Cadherin-E, Cadherin-P, Calcitonin, Calcium Pump ATPase, Caldesmon, Calmodulin, Calponin, Calretinin, Casein, Caspase 1, Caspase 2, Caspase 3, Caspase 5, Caspase 6 (Mch 2), Caspase 7 (Mch 3), Caspase 8 (FLICE), Caspase 9, Catenin alpha, Catenin beta, Catenin gamma, Cathepsin D, CCK-8, CD1, CD10, CD100/ Leukocyte Semaphorin, CD105, CD106/VCAM, CD115/c-fms/CSF-1R/M-CSFR, CD137 (4-1BB), CD138, CD14, CD15, CD155/PVR (Polio Virus Receptor), CD16, CD165, CD18, CD1a, CD1b, CD2, CD20, CD21, CD23, CD231, CD24, CD25/IL-2 Receptor a, CD26/DPP IV, CD29, CD30 (Reed-Sternberg Cell Marker), CD32/Fcg Receptor II, CD35/CR1, CD36GPIIIb/ GPIV, CD3zeta, CD4, CD40, CD42b, CD43, CD45/T200/LCA, CD45RB, CD45RO, CD46, CD5, CD50/ICAM-3, CD53, CD54/ICAM-1, CD56/NCAM-1, CD57, CD59/MACIF/MIRE/Protectin, CD6, CD61/ Platelet Glycoprotein IIIA, CD63, CD68, CD71/ Transferrin Receptor, CD79a mb-1, CD79b, CD8, CD81/TAPA-1, CD84, CD9, CD94, CD95/Fas, CD98, CDC14A Phosphatase, CDC25C, CDC34, CDC37, CDC47, CDC6, cdh1, Cdk1/p34cdc2, Cdk2, Cdk3, Cdk4, CdkS, Cdk7, Cdk8, CDw17, CDw60, CDw75, CDw78, CEA/CD66e, c-erbB-2/HER-2/neu Ab-1 (21N), c-erbB-4/HER-4, c-fos, Chk1, Chorionic Gonadotropin beta (hCG-beta), Chromogranin A, CIDE-A, CIDE-B, CITED1, c-jun, Clathrin, claudin 11, Claudin 2, Claudin 3, Claudin 4, Claudin 5, CLAUDIN 7, Claudin-1, CNPase, Collagen II, Collagen IV, Collagen IX, Collagen VII, Connexin 43, COX2, CREB, CREB-Binding Protein, Cryptococcus neoformans, c-Src, Cullin-1 , (CUL-1), Cullin-2 (CUL-2), Cullin-3 (CUL-3) CXCR4/Fusin, Cyclin B1, Cyclin C, Cyclin D1, Cyclin D3, Cyclin E, Cyclin E2, Cystic Fibrosis Transmembrane Regulator, Cytochrome c, D4-GDI, Daxx, DcR1, DcR2/TRAIL- R4/TRUNDD, Desmin, DFF40 (DNA Fragmentation Factor 40)/CAD, DFF45/ICAD, DJ-1, DNA Ligase I, DNA Polymerase Beta, DNA Polymerase Gamma, DNA Primase (p49), DNA Primase (p58), DNA-PKcs, DP-2, DR3, DR5, Dysferlin, Dystrophin, E2F-1, E2F-2, E2F-3, E2F-4, E2F-5, E3-binding protein (ARM1), EGFR, EMA/CA15-3/MUC-1, Endostatin, Epithelial Membrane Antigen (EMA/CA15-3/MUC-1), Epithelial Specific Antigen, ER beta, ER Ca + 2 ATPase2, ERCC1, Erk1, ERK2, Estradiol, Estriol, Estrogen Receptor, Exo1, Ezrin/p81/80K/Cytovillin, F.VIII/VWF, Factor VIII Related Antigen, FADD (FAS-Associated death domain-containing protein), Fascin, Fas-ligand, Ferritin, FGF-1, FGF-2, FHIT, Fibrillin-1, Fibronectin, Filaggrin, Filamin, FITC, Fli-1, FLIP, Flk-1/KDR/ VEGFR2, Flt-1/VEGFR1, Flt-4, Fra2, FSH, FSH-b, Fyn, Ga0, Gab-1, GABA a Receptor 1, GAD65, Gai1, Gamma Glutamyl Transferase (gGT), Gamma Glutamylcysteine Synthetase(GCS)/Glutamate-cysteine Ligase, GAPDH, Gastrin 1, GCDFP-15, G-CSF, GFAP, Glicentin, Glucagon, Glucose-Regulated Protein 94, GluR 2/3, GluR1, GluR4, GluR6/7, GLUT-1, GLUT-3, Glycogen Synthase Kinase 3b (GSK3b), Glycophorin A, GM- CSF, GnRH Receptor, Golgi Complex, Granulocyte, Granzyme B, Grb2, Green Fluorescent Protein (GFP), GRIP1, Growth Hormone (hGH), GSK-3, GST, GSTmu, H.Pylori, HDAC1, HDJ-2/DNAJ, Heat Shock Factor 1, Heat Shock Factor 2, Heat Shock Protein 27/hsp27, Heat Shock Protein 60/hsp60, Heat Shock Protein 70/hsp70, Heat Shock Protein 75/hsp75, Heat Shock Protein 90a/hsp86, Heat Shock Protein 90b/hsp84, Helicobacter pylori, Heparan Sulfate Proteoglycan, Hepatic Nuclear Factor-3B, Hepatocyte, Hepatocyte Factor Homologue-4, Hepatocyte Growth Factor, Heregulin, HIF-1a, Histone H1, hPL, HPV 16, HPV 16-E7, HRP, Human Sodium Iodide Symporter (hNIS), I-FLICE/CASPER, IFN gamma, IgA, IGF-1R, IGF-I, IgG, IgM (m-Heavy Chain), I-Kappa-B Kinase b (IKKb), IL-1 alpha, IL-1 beta, IL-10, IL-10R, IL17, IL-2, IL-3, IL-30, IL-4, IL-5, IL-6, IL-8, Inhibin alpha, Insulin, Insulin Receptor, Insulin Receptor Substrate-1, Int-2 Oncoprotein, Integrin beta5, Interferon-a(II), Interferon-g, Involucrin, IP10/CRG2, IPO-38 Proliferation Marker, IRAK, ITK, JNK Activating kinase (JKK1), Kappa Light Chain, Keratin 10, Keratin 10/13, Keratin 14, Keratin 15, Keratin 16, Keratin 18, Keratin 19, Keratin 20, Keratin 5/6/18, Keratin 5/8, Keratin 8, Keratin 8 (phospho-specific Ser73), Keratin 8/18, Keratin (LMW), Keratin (Multi), Keratin (Pan), Ki67, Ku (p70/p80), Ku (p80), L1 Cell Adhesion Molecule, Lambda Light Chain, Laminin B1/b1, Laminin B2/g1, Laminin Receptor, Laminin-s, Lck, Lck (p56lck), Leukotriene (C4, D4, E4), LewisA, LewisB, LH, L-Plastin, LRP/MVP, Luciferase, Macrophage, MADD, MAGE-1, Maltose Binding Protein, MAP1B, MAP2a, b, MART- 1/Melan-A, Mast Cell Chymase, Mcl-1, MCM2, MCM5, MDM2, Medroxyprogesterone Acetate (MPA), Mek1, Mek2, Mek6, Mekk-1, Melanoma (gp100), mGluR1, mGluR5, MGMT, MHC I (HLA25 and HLA-Aw32), MHC I (HLA-A), MHC I (HLA-A, B, C), MHC I (HLA-B), MHC II (HLA-DP and DR), MHC II (HLA-DP), MHC II (HLA-DQ), MHC II (HLA-DR), MHC II (HLA-DR) Ia, Microphthalmia, Milk Fat Globule Membrane Protein, Mitochondria, MLH1, MMP-1 (Collagenase-I), MMP-10 (Stromilysin-2), MMP-11 (Stromelysin-3), MMP-13 (Collagenase-3), MMP-14/MT1-MMP, MMP-15/MT2-MMP, MMP-16/MT3-MMP, MMP-19, MMP-2 (72 kDa Collagenase IV), MMP-23, MMP-7 (Matrilysin), MMP-9 (92 kDa Collagenase IV), Moesin, mRANKL, Muc-1, Mucin 2, Mucin 3 (MUC3), Mucin SAC, MyD88, Myelin/ Oligodendrocyte, Myeloid Specific Marker, Myeloperoxidase, MyoD1, Myogenin, Myoglobin, Myosin Smooth Muscle Heavy Chain, Nck, Negative Control for Mouse IgG1, Negative Control for Mouse IgG2a, Negative Control for Mouse IgG3, Negative Control for Mouse IgM, Negative Control for Rabbit IgG, Neurofilament, Neurofilament (160 kDa), Neurofilament (200 kDa), Neurofilament (68 kDa), Neuron Specific Enolase, Neutrophil Elastase, NF kappa B/p50, NF kappa B/p65 (Rel A), NGF-Receptor (p75NGFR), brain Nitric Oxide Synthase (bNOS), endothelial Nitric Oxide Synthase (eNOS), nm23, NOS-i, NOS-u, Notch, Nucleophosmin (NPM), NuMA, O ct-1, Oct-2/, Oct-3/, Ornithine Decarboxylase, Osteopontin, p130, p130cas, p14ARF, p15INK4b, p16INK4a, p170, p170/MDR-1, p18INK4c, p19ARF, p19Skp1, p21WAF1, p27Kip1, p300/ CBP, p35nck5a, P504S, p53, p57Kip2 Ab-7, p63 (p53 Family Member), p73, p73a, p73a/b, p95VAV, Parathyroid Hormone, Parathyroid Hormone Receptor Type 1, Parkin, PARP, PARP (Poly ADP-Ribose Polymerase), Pax-5, Paxillin, PCNA, PCTAIRE2, PDGF, PDGFR alpha, PDGFR beta, Pds1, Perforin, PGP9.5, PHAS-I, PHAS-II, Phospho-Ser/Thr/Tyr, Phosphotyrosine, PLAP, Plasma Cell Marker, Plasminogen, PLC gamma 1, PMP-22, Pneumocystis jiroveci, PPAR-gamma, PR3 (Proteinase 3), Presenillin, Progesterone, Progesterone Receptor, Progesterone Receptor (phospho-specific)-Serine 190, Progesterone Receptor (phospho-specific)-Serine 294, Prohibitin, Prolactin, Prolactin Receptor, Prostate Apoptosis Response Protein-4, Prostate Specific Acid Phosphatase, Prostate Specific Antigen, pS2, PSCA, Rabies Virus, RAD1, Rad51, Raf1, Raf-1 (Phospho-specific), RAIDD, Ras, Rad18, Renal Cell Carcinoma, Ret Oncoprotein, Retinoblastoma, Retinoblastoma (Rb) (Phospho-specific Serine608), Retinoic Acid Receptor (b), Retinoid X Receptor (hRXR), Retinol Binding Protein, Rhodopsin (Opsin), ROC, RPA/p32, RPA/p70, Ruv A, Ruv B, Ruv C, S100, S100A4, S100A6, SHP-1, SIM Ag (SIMA-4D3), SIRP a1, sm, SODD (Silencer of Death Domain), Somatostatin Receptor-I, SRC1 (Steroid Receptor Co activator-1) Ab-1, SREBP-1 (Sterol Regulatory Element Binding Protein-1), SRF (Serum Response Factor), Stat-1, Stat3, Stat5, Stat5a, Stat5b, Stat6, Streptavidin, Superoxide Dismutase, Surfactant Protein A, Surfactant Protein B, Surfactant Protein B (Pro), Survivin, SV40 Large T Antigen, Syk, Synaptophysin, Synuclein, Synuclein beta, Synuclein pan, TACE (TNF-alpha converting enzyme)/ADAM17, TAG-72, tau, TdT, Tenascin, Testosterone, TGF beta 3, TGF-beta 2, Thomsen-Friedenreich Antigen, Thrombospondin, Thymidine Phosphorylase, Thymidylate Synthase, Thymine Glycols, Thyroglobulin, Thyroid Hormone Receptor beta, Thyroid Hormone Receptor, Thyroid Stimulating Hormone (TSH), TID-1, TIMP-1, TIMP-2, TNF alpha, TNFa, TNR-R2, Topo II beta, Topoisomerase IIa, Toxoplasma Gondii, TR2, TRADD, Transforming Growth Factor a, Transglutaminase II, TRAP, Tropomyosin, TRP75/ gp75, TrxR2, TTF-1, Tubulin, Tubulin-a, Tubulin-b, Tyrosinase, Ubiquitin, UCP3, uPA, Urocortin, Vacular Endothelial Growth Factor(VEGF), Vimentin, Vinculin, Vitamin D Receptor (VDR), von Hippel-Lindau Protein, , Wnt-1, Xanthine Oxidase, XPA, XPF, XPG XRCC1, XRCC2, ZAP-70, Zip kinase Known Cancer ABL1, ABL2, ACSL3, AF15Q14, AF1Q, AF3p21, Genes AF5q31, AKAP9, AKT1, AKT2, ALDH2, ALK, ALO17, APC, ARHGEF12, ARHH, ARID1A, ARID2, ARNT, ASPSCR1, ASXL1, ATF1, ATIC, ATM, ATRX, BAP1, BCL10, BCL11A, BCL11B, BCL2, BCL3, BCL5, BCL6, BCL7A, BCL9, BCOR, BCR, BHD, BIRC3, BLM, BMPR1A, BRAF, BRCA1, BRCA2, BRD3, BRD4, BRIP1, BTG1, BUB1B, C12orf9, C15orf21, C15orf55, C16orf75, CANT1, CARD11, CARS, CBFA2T1, CBFA2T3, CBFB, CBL, CBLB, CBLC, CCNB1IP1, CCND1, CCND2, CCND3, CCNE1, CD273, CD274, CD74, CD79A, CD79B, CDH1, CDH11, CDK12, CDK4, CDK6, CDKN2A, CDKN2a(p14), CDKN2C, CDX2, CEBPA, CEP1, CHCHD7, CHEK2, CHIC2, CHN1, CIC, CIITA, CLTC, CLTCL1, CMKOR1, COL1A1, COPEB, COX6C, CREB1, CREB3L1, CREB3L2, CREBBP, CRLF2, CRTC3, CTNNB1, CYLD, D10S170, DAXX, DDB2, DDIT3, DDX10, DDX5, DDX6, DEK, DICER1, DNMT3A, DUX4, EBF1, EGFR, EIF4A2, ELF4, ELK4, ELKS, ELL, ELN, EML4, EP300, EPS15, ERBB2, ERCC2, ERCC3, ERCC4, ERCC5, ERG, ETV1, ETV4, ETV5, ETV6, EVIL EWSR1, EXT1, EXT2, EZH2, FACL6, FAM22A, FAM22B, FAM46C, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, FBXO11, FBXW7, FCGR2B, FEV, FGFR1, FGFR1OP, FGFR2, FGFR3, FH, FHIT, FIP1L1, FLI1, FLJ27352, FLT3, FNBP1, FOXL2, FOXO1A, FOXO3A, FOXP1, FSTL3, FUBP1, FUS, FVT1, GAS7, GATA1, GATA2, GATA3, GMPS, GNA11, GNAQ, GNAS, GOLGA5, GOPC, GPC3, GPHN, GRAF, HCMOGT-1, HEAB, HERPUD1, HEY1, HIP1, HIST1H4I, HLF, HLXB9, HMGA1, HMGA2, HNRNPA2B1, HOOK3, HOXA11, HOXA13, HOXA9, HOXC11, HOXC13, HOXD11, HOXD13, HRAS, HRPT2, HSPCA, HSPCB, IDH1, IDH2, IGH@, IGK@, IGL@, IKZF1, IL2, IL21R, IL6ST, IL7R, IRF4, IRTA1, ITK, JAK1, JAK2, JAK3, JAZF1, JUN, KDM5A, KDM5C, KDM6A, KDR, KIAA1549, KIT, KLK2, KRAS, KTN1, LAF4, LASP1, LCK, LCP1, LCX, LHFP, LIFR, LMO1, LMO2, LPP, LYL1, MADH4, MAF, MAFB, MALT1, MAML2, MAP2K4, MDM2, MDM4, MDS1, MDS2, MECT1, MED12, MEN1, MET, MITF, MKL1, MLF1, MLH1, MLL, MLL2, MLL3, MLLT1, MLLT10, MLLT2, MLLT3, MLLT4, MLLT6, MLLT7, MN1, MPL, MSF, MSH2, MSH6, MSI2, MSN, MTCP1, MUC1, MUTYH, MYB, MYC, MYCL1, MYCN, MYD88, MYH11, MYH9, MYST4, NACA, NBS1, NCOA1, NCOA2, NCOA4, NDRG1, NF1, NF2, NFE2L2, NFIB, NFKB2, NIN, NKX2-1, NONO, NOTCH1, NOTCH2, NPM1, NR4A3, NRAS, NSD1, NTRK1, NTRK3, NUMA1, NUP214, NUP98, OLIG2, OMD, P2RY8, PAFAH1B2, PALB2, PAX3, PAX5, PAX7, PAX8, PBRM1, PBX1, PCM1, PCSK7, PDE4DIP, PDGFB, PDGFRA, PDGFRB, PER1, PHOX2B, PICALM, PIK3CA, PIK3R1, PIM1, PLAG1, PML, PMS1, PMS2, PMX1, PNUTL1, POU2AF1, POU5F1, PPARG, PPP2R1A, PRCC, PRDM1, PRDM16, PRF1, PRKAR1A, PRO1073, PSIP2, PTCH, PTEN, PTPN11, RAB5EP, RAD51L1, RAF1, RALGDS, RANBP17, RAP1GDS1, RARA, RB1, RBM15, RECQL4, REL, RET, ROS1, RPL22, RPN1, RUNDC2A, RUNX1, RUNXBP2, SBDS, SDH5, SDHB, SDHC, SDHD, SEPT6, SET, SETD2, SF3B1, SFPQ, SFRS3, SH3GL1, SIL, SLC45A3, SMARCA4, SMARCB1, SMO, SOCS1, SOX2, SRGAP3, SRSF2, SS18, SS18L1, SSH3BP1, SSX1, SSX2, SSX4, STK11, STL, SUFU, SUZ12, SYK, TAF15, TALL TAL2, TCEA1, TCF1, TCF12, TCF3, TCF7L2, TCL1A, TCL6, TET2, TFE3, TFEB, TFG, TFPT, TFRC, THRAP3, TIF1, TLX1, TLX3, TMPRSS2, TNFAIP3, TNFRSF14, TNFRSF17, TNFRSF6, TOP1, TP53, TPM3, TPM4, TPR, TRA@, TRB@, TRD@, TRIM27, TRIM33, TRIP11, TSC1, TSC2, TSHR, TTL, U2AF1, USP6, VHL, VTI1A, WAS, WHSC1, WHSC1L1, WIF1, WRN, WT1, WTX, XPA, XPC, XPO1, YWHAE, ZNF145, ZNF198, ZNF278, ZNF331, ZNF384, ZNF521, ZNF9, ZRSR2 Known Cancer AR, androgen receptor; ARPC1A, actin-related Genes protein complex 2/3 subunit A; AURKA, Aurora kinase A; BAG4, BCl-2 associated anthogene 4; BCl212, BCl-2 like 2; BIRC2, Baculovirus IAP repeat containing protein 2; CACNA1E, calcium channel voltage dependent alpha-1E subunit; CCNE1, cyclin E1; CDK4, cyclin dependent kinase 4; CHD1L, chromodomain helicase DNA binding domain 1-like; CKS1B, CDC28 protein kinase 1B; COPS3, COP9 subunit 3; DCUN1D1, DCN1 domain containing protein 1; DYRK2, dual specificity tyrosine phosphorylation regulated kinase 2; EEF1A2, eukaryotic elongation transcription factor 1 alpha 2; EGFR, epidermal growth factor receptor; FADD, Fas- associated via death domain; FGFR1, fibroblast growth factor receptor 1, GATA6, GATA binding protein 6; GPC5, glypican 5; GRB7, growth factor receptor bound protein 7; MAP3K5, mitogen activated protein kinase kinase kinase 5; MED29, mediator complex subunit 5; MITF, microphthalmia associated transcription factor; MTDH, metadherin; NCOA3, nuclear receptor coactivator 3; NKX2-1, NK2 homeobox 1; PAK1, p21/CDC42/RAC1-activated kinase 1; PAX9, paired box gene 9; PIK3CA, phosphatidylinositol-3 kinase catalytic a; PLA2G10, phopholipase A2, group X; PPM1D, protein phosphatase magnesium-dependent 1D; PTK6, protein tyrosine kinase 6; PRKCI, protein kinase C iota; RPS6KB1, ribosomal protein s6 kinase 70 kDa; SKP2, s-phase kinase associated protein; SMURF1, sMAD specific E3 ubiquitin protein ligase 1; SHH, sonic hedgehog homologue; STARD3, sTAR-related lipid transfer domain containing protein 3; YWHAQ, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta isoform; ZNF217, zinc finger protein 217 Mitotic Related Aurora kinase A (AURKA); Aurora kinase B Cancer Genes (AURKB); Baculoviral IAP repeat-containing 5, survivin (BIRC5); Budding uninhibited by benzimidazoles 1 homolog (BUB1); Budding uninhibited by benzimidazoles 1 homolog beta, BUBR1 (BUB1B); Budding uninhibited by benzimidazoles 3 homolog (BUB3); CDC28 protein kinase regulatory subunit 1B (CKS1B); CDC28 protein kinase regulatory subunit 2 (CKS2); Cell division cycle 2 (CDC2)/CDK1 Cell division cycle 20 homolog (CDC20); Cell division cycle-associated 8, borealin (CDCA8); Centromere protein F, mitosin (CENPF); Centrosomal protein 110 kDa (CEP110); Checkpoint with forkhead and ring finger domains (CHFR); Cyclin B1 (CCNB1); Cyclin B2 (CCNB2); Cytoskeleton-associated protein 5 (CKAP5/ch-TOG); Microtubule-associated protein RP/EB family member 1. End-binding protein 1, EB1 (MAPRE1); Epithelial cell transforming sequence 2 oncogene (ECT2); Extra spindle poles like 1, separase (ESPL1); Forkhead box M1 (FOXM1); H2A histone family family, member X (H2AFX); Kinesin member 4A (KIF4A); Kinetochore-associated 1 (KNTC1/ROD); Kinetochore-associated 2; highly expressed in cancer 1 (KNTC2/HEC1); Large tumor suppressor, homolog 1 (LATS1); Large tumor suppressor, homolog 2 (LATS2); Mitotic arrest deficient-like 1; MAD1 (MAD1L1); Mitotic arrest deficient-like 2; MAD2 (MAD2L1); Mps1 protein kinase (TTK); Never in mitosis gene a-related kinase 2 (NEK2); Ninein, GSK3b interacting protein (NIN); Non-SMC condensin I complex, subunit D2 (NCAPD2/CNAP1); Non-SMC condensin I complex, subunit H (NACPH/CAPH); Nuclear mitotic apparatus protein 1 (NUMA1); Nucleophosmin (nucleolar phosphoprotein B23, numatrin); (NPM1); Nucleoporin (NUP98); Pericentriolar material 1 (PCM1); Pituitary tumor-transforming 1, securin (PTTG1); Polo-like kinase 1 (PLK1); Polo-like kinase 4 (PLK4/SAK); s Protein (peptidylprolyl cis/tran isomerase) NIMA-interacting 1 (PIN1); Protein regulator of cytokinesis 1 (PRC1); RAD21 homolog (RAD21); Ras association (Ra1GDS/AF-6); domain family 1 (RASSF1); Stromal antigen 1 (STAG1); Synuclein-c, breast cancer- specific protein 1 (SNCG, BCSG1); Targeting protein for Xklp2 (TPX2); Transforming, acidic coiled-coil containing protein 3 (TACC3); Ubiquitin-conjugating enzyme E2C (UBE2C); Ubiquitin-conjugating enzyme E2I (UBE2I/UBC9); ZW10 interactor, (ZWINT); ZW10, kinetochore-associated homolog (ZW10); Zwilch, kinetochore-associated homolog (ZWILCH) Ribonucleoprotein Argonaute family member, Ago1, Agog, complexes Ago3, Ago4, GW182 (TNRC6A), TNRC6B, TNRC6C, HNRNPA2B1, HNRPAB, ILF2, , NCL (Nucleolin), NPM1 (Nucleophosmin) RPL10A, RPL5, RPLP1, RPS12, RPS19, SNRPG, TROVE2, apolipoprotein, apolipoprotein A, apo A-I, apo A-II, apo A-IV, apo A-V, apolipoprotein B, apo B48, apo B100, apolipoprotein C, apo C-I, apo C-II, apo C-III, apo C-IV, apolipoprotein D (ApoD), apolipoprotein E (ApoE), apolipoprotein H 2, (ApoH), apolipoprotein L, APOL1, APOL APOL3, APOL4, APOL5, APOL6, APOLD1 Cytokine Receptors 4-1BB, ALCAM, B7-1, BCMA, CD14, CD30, CD40 Ligand, CEACAM-1, DR6, Dtk, Endoglin, ErbB3, E-Selectin, Fas, Flt-3L, GITR, HVEM, ICAM-3, IL-1 R4, IL-1 RI, IL-10 Rbeta, IL-17R, IL-2Rgamma, IL-21R, LIMPII, Lipocalin-2, L-Selectin, LYVE-1, MICA, MICB, NRG1-beta1, PDGF Rbeta, PECAM-1, RAGE, TIM-1, TRAIL R3, Trappin-2, uPAR, VCAM-1, XEDAR Prostate and ErbB3, RAGE, Trail R3 colorectal cancer vesicles Colorectal cancer IL-1 alpha, CA125, Filamin, Amyloid A vesicles Colorectal cancer v Involucrin, CD57, Prohibitin, Thrombospondin, adenoma vesicles Laminin B1/b1, Filamin, 14.3.3 gamma, 14.3.3 Pan Colorectal Involucrin, Prohibitin, Laminin B1/b1, IL-3, adenoma vesicles Filamin, 14.3.3 gamma, 14.3.3 Pan, MMP-15/ MT2-MMP, hPL, Ubiquitin, and mRANKL Brain cancer Prohibitin, CD57, Filamin, CD18, b-2-Microglobulin, vesicles IL-2, IL-3, CD16, p170, Keratin 19, Pds1, Glicentin, SRF (Serum Response Factor), E3-binding protein (ARM1), Collagen II, SRC1 (Steroid Receptor Coactivator-1) Ab-1, Caldesmon, GFAP, TRP75/gp75, alpha-1- antichymotrypsin, Hepatic Nuclear Factor-3B, PLAP, Tyrosinase, NF kappa B/p50, Melanoma (gp100), Cyclin E, 6-Histidine, Mucin 3 (MUC3), TdT, CD21, XPA, Superoxide Dismutase, Glycogen Synthase Kinase 3b (GSK3b), CD54/ICAM-1, Thrombospondin, Gai1, CD79a mb-1, IL-1 beta, Cytochrome c, RAD1, bcl-X, CD50/ICAM-3, Neurofilament, Alkaline Phosphatase (AP), ER Ca + 2 ATPase2, PCNA, F.VIII/VWF, SV40 Large T Antigen, Paxillin, Fascin, CD165, GRIP1, Cdk8, Nucleophosmin (NPM), alpha-1-antitrypsin, CD32/Fcg Receptor II, Keratin 8 (phospho- specific Ser73), DRS, CD46, TID-1, MHC II (HLA-DQ), Plasma Cell Marker, DR3, Calmodulin, AIF (Apoptosis Inducing Factor), DNA Polymerase Beta, Vitamin D Receptor (VDR), Bcl10/CIPER/CLAP/mE10, Neuron Specific Enolase, CXCR4/Fusin, Neurofilament (68 kDa), PDGFR, beta, Growth Hormone (hGH), Mast Cell Chymase, Ret Oncoprotein, and Phosphotyrosine Melanoma Caspase 5, Thrombospondin, Filamin, Ferritin, vesicles 14.3.3 gamma, 14.3.3 Pan, CD71/Transferrin Receptor, and Prostate Apoptosis Response Protein-4 Head and neck 14.3.3 Pan, Filamin, 14.3.3 gamma, CD71/ cancer vesicles Transferrin Receptor, CD30, Cdk5, CD138, Thymidine Phosphorylase, Ruv 5, Thrombospondin, CD1, Von Hippel-Lindau Protein, CD46, Rad51, Ferritin, c-Abl, Actin, Muscle Specific, LewisB Membrane carbonic anhydrase IX, B7, CCCL19, CCCL21, proteins CSAp, HER-2/neu, BrE3, CD1, CD1a, CD2, CD3, CD4, CD5, CD8, CD11A, CD14, CD15, CD16, CD18, CD19, CD20, CD21, CD22, CD23, CD25, CD29, CD30, CD32b, CD33, CD37, CD38, CD40, CD4OL, CD44, CD45, CD46, CD52, CD54, CD55, CD59, CD64, CD67, CD70, CD74, CD79a, CD80, CD83, CD95, CD126, CD133, CD138, CD147, CD154, CEACAMS, CEACAM-6, alpha-fetoprotein (AFP), VEGF, ED-B fibronectin, EGP-1, EGP-2, EGF receptor (ErbB1), ErbB2, ErbB3, Factor H, FHL-1, Flt-3, folate receptor, Ga 733, GROB, HMGB-1, hypoxia inducible factor (HIF), HM1.24, HER-2/neu, insulin-like growth factor (ILGF), IFN-y, IFN-a, IL-f3, IL-2R, IL-4R, IL-6R, IL-13R, IL-15R, IL-17R, IL-18R, IL-2, IL-6, IL-8, IL-12, IL-15, IL-17, IL-18, IL-25, IP-10, IGF-1R, Ia, HM1.24, gangliosides, HCG, HLA-DR, CD66a-d, MAGE, mCRP, MCP-1, MIP-1A, MIP-1B, macrophage migration-inhibitory factor (MIF), MUC1, MUC2, MUC3, MUC4, MUC5, placental growth factor (P1GF), PSA (prostate-specific antigen), PSMA, PSMA dimer, PAM4 antigen, NCA-95, NCA-90, A3, A33, Ep-CAM, KS-1, Le(y), mesothelin, S100, tenascin, TAC, Tn antigen, Thomas-Friedenreich antigens, tumor necrosis antigens, tumor angiogenesis antigens, TNF-α, TRAIL receptor (R1 and R2), VEGFR, RANTES, T101, cancer stem cell antigens, complement factors C3, C3a, C3b, C5a, C5 Cluster of CD1, CD2, CD3, CD4, CD5, CD6, CD7, CD8, Differentiation CD9, CD10, CD11a, CD11b, CD11c, (CD) proteins CD12w, CD13, CD14, CD15, CD16, CDw17, CD18, CD19, CD20, CD21, CD22, CD23, CD24, CD25, CD26, CD27, CD28, CD29, CD30, CD31, CD32, CD33, CD34, CD35, CD36, CD37, CD38, CD39, CD40, CD41, CD42, CD43, CD44, CD45, CD46, CD47, CD48, CD49a, CD49b, CD49c, CD49d, CD49e, CD49f, CD53, CD54, CD55, CD56, CD57, CD58, CD59, CD61, CD62E, CD62L, CD62P, CD63, CD68, CD69, CD71, CD72, CD73, CD74, CD80, CD81, CD82, CD83, CD86, CD87, CD88, CD89, CD90, CD91, CD95, CD96, CD100, CD103, CD105, CD106, CD107, CD107a, CD107b, CD109, CD117, CD120, CD127, CD133, CD134, CD135, CD138, CD141, CD142, CD143, CD144, CD147, CD151, CD152, CD154, CD156, CD158, CD163, CD165, CD166, CD168, CD184, CDw186, CD195, CD197, CD209, CD202a, CD220, CD221, CD235a, CD271, CD303, CD304, CD309, CD326 Interleukin (IL) IL-1, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8 or proteins CXCL8, IL-9, IL-10, IL-11, IL-12, IL-13, IL- 14, IL-15, IL-16, IL-17, IL-18, IL-19, IL-20, IL-21, IL-22, IL-23, IL-24, IL-25, IL-26, IL-27, IL-28, IL-29, IL-30, IL-31, IL-32, IL-33, IL-35, IL-36 IL receptors CD121a/IL1R1, CD121b/IL1R2, CD25/IL2RA, CD122/IL2RB, CD132/IL2RG, CD123/IL3RA, CD131/IL3RB, CD124/IL4R, CD132/IL2RG, CD125/IL5RA, CD131/IL3RB, CD126/IL6RA, CD130/IR6RB, CD127/IL7RA, CD132/IL2RG, CXCR1/IL8RA, CXCR2/IL8RB/CD128, , CD129/IL9R, CD210/IL10RA CDW210B/IL10RB, IL11RA, CD212/IL12RB1, IR12RB2, IL13R, IL15RA, CD4, CDw217/IL17RA, IL17RB, CDw218a/IL18R1, IL20R, IL20R, IL21R, IL22R, IL23R, IL20R, LY6E, IL20R1, IL27RA, IL28R, IL31RA Mucin (MUC) MUC1, MUC2, MUC3A, MUC3B, MUC4, proteins MUC5AC, MUC5B, MUC6, MUC7, MUC8, MUC12, MUC13, MUC15, MUC16, MUC17, MUC19, and MUC20 MUC1 isoforms mucin-1 isoform 2 precursor or mature form (NP_001018016.1), mucin-1 isoform 3 precursor or mature form (NP_001018017.1), mucin-1 isoform 5 precursor or mature form (NP_001037855.1), mucin-1 isoform 6 precursor or mature form (NP_001037856.1), mucin- 1 isoform 7 precursor or mature form (NP_001037857.1), mucin-1 isoform 8 precursor or mature form (NP_001037858.1), mucin-1 isoform 9 precursor or mature form (NP_001191214.1), mucin-1 isoform 10 precursor or mature form (NP_001191215.1), mucin-1 isoform 11 precursor or mature form (NP_001191216.1), mucin-1 isoform 12 precursor or mature form (NP_001191217.1), mucin-1 isoform 13 precursor or mature form (NP_001191218.1), mucin-1 isoform 14 precursor or mature form (NP_001191219.1), mucin-1 isoform 15 precursor or mature form (NP_001191220.1), mucin-1 isoform 16 precursor or mature form (NP_001191221.1), mucin-1 isoform 17 precursor or mature form (NP_001191222.1), mucin-1 isoform 18 precursor or mature form (NP_001191223.1), mucin-1 isoform 19 precursor or mature form (NP_001191224.1), mucin-1 isoform 20 precursor or mature form (NP_001191225.1), mucin-1 isoform 21 precursor or mature form (NP_001191226.1), mucin-1 isoform 1 precursor or mature form (NP_002447.4), ENSP00000357380, ENSP00000357377, ENSP00000389098, ENSP00000357374, ENSP00000357381, ENSP00000339690, ENSP00000342814, ENSP00000357383, ENSP00000357375, ENSP00000338983, ENSP00000343482, ENSP00000406633, ENSP00000388172, ENSP00000357378, P15941-1, P15941-2, P15941-3, P15941-4, P15941-5, P15941-6, P15941-7, P15941-8, P15941-9, P15941-10, secreted isoform, membrane bound isoform, CA 27.29 (BR 27.29), CA 15-3, PAM4 reactive antigen, underglycosylated isoform, unglycosylated isoform, CanAg antigen MUC1 interacting ABL1, SRC, CTNND1, ERBB2, GSK3B, JUP, proteins PRKCD, APC, GALNT1, GALNT10, GALNT12, JUN, LCK, OSGEP, ZAP70, CTNNB1, EGFR, SOS1, ERBB3, ERBB4, GRB2, ESR1, GALNT2, GALNT4, LYN, TP53, C1GALT1, C1GALT1C1, GALNT3, GALNT6, GCNT1, GCNT4, MUC12, MUC13, MUC15, MUC17, MUC19, MUC2, MUC20, MUC3A, MUC4, MUC5B, MUC6, MUC7, MUCL1, ST3GAL1, ST3GAL3, ST3GAL4, ST6GALNAC2, B3GNT2, B3GNT3, B3GNT4, B3GNT5, B3GNT7, B4GALT5, GALNT11, GALNT13, GALNT14, GALNT5, GALNT8, GALNT9, ST3GAL2, ST6GAL1, ST6GALNAC4, GALNT15, MYOD1, SIGLEC1, IKBKB, TNFRSF1A, IKBKG, MUC1 Tumor markers Alphafetoprotein (AFP), Carcinoembryonic antigen (CEA), CA-125, MUC-1, Epithelial tumor antigen (ETA), Tyrosinase, Melanoma-associated antigen (MAGE), p53 Tumor markers Alpha fetoprotein (AFP), CA15-3, CA27-29, CA19-9, CA-125, Calretinin, Carcinoembryonic antigen, CD34, CD99, CD117, Chromogranin, Cytokeratin (various types), Desmin, Epithelial membrane protein (EMA), Factor VIII, CD31 FL1, Glial fibrillary acidic protein (GFAP), Gross cystic disease fluid protein (GCDFP-15), HMB-45, Human chorionic gonadotropin (hCG), immunoglobulin, inhibin, keratin (various types), PTPRC (CD45), lymphocyte marker (various types, MART-1 (Melan-A), Myo D1, muscle-specific actin (MSA), neurofilament, neuron-specific enolase (NSE), placental alkaline phosphatase (PLAP), prostate-specific antigen, S100 protein, smooth muscle actin (SMA), synaptophysin, thyroglobulin, thyroid transcription factor-1, ntin Tumor M2-PK, vime Cell adhesion Immunoglobulin superfamily CAMs (IgSF CAMs), molecule (CAMs) N-CAM (Myelin protein zero), ICAM (1, 5), VCAM-1, PE-CAM, L1-CAM, Nectin (PVRL1, PVRL2, PVRL3), Integrins, LFA-1 (CD11a + CD18), Integrin alphaXbeta2 (CD11c + CD18), Macrophage-1 antigen (CD11b + CD18), VLA-4 (CD49d + CD29), Glycoprotein Hb/IIIa (ITGA2B + ITGB3), Cadherins, CDH1, CDH2, CDH3, Desmosomal, Desmoglein (DSG1, DSG2, DSG3, DSG4), Desmocollin (DSC1, DSC2, DSC3), Protocadherin, PCDH1, T-cadherin, CDH4, CDH5, CDH6, CDH8, CDH11, CDH12, CDH15, CDH16, CDH17, CDH9, CDH10, Selectins, E- selectin, L-selectin, P-selectin, Lymphocyte homing receptor: CD44, L-selectin, integrin (VLA-4, LFA-1), Carcinoembryonic antigen (CEA), CD22, CD24, CD44, CD146, CD164 Annexins ANXA1; ANXA10 ; ANXA11; ANXA13; ANXA2; ANXA3; ANXA4; ANXAS; ANXA6; ANXA7; ANXA8; ANXA8L1; ANXA8L2; ANXA9 Cadherins CDH1, CDH2, CDH12, CDH3, Deomoglein, (“calcium- DSG1, DSG2, DSG3, DSG4, Desmocollin, dependent DSC1, DSC2, DSC3, Protocadherins, PCDH1, adhesion”) PCDH10, PCDH11x, PCDH11y, PCDH12, FAT, FAT2, FAT4, PCDH15, PCDH17, PCDH18, PCDH19; PCDH20; PCDH7, PCDH8, PCDH9, PCDHAL PCDHA10, PCDHA11, PCDHA12, PCDHA13, PCDHA2, PCDHA3, PCDHA4, PCDHAS, PCDHA6, PCDHA7, PCDHA8, PCDHA9, PCDHAC1, PCDHAC2, PCDHB1, PCDHB10, PCDHB11, PCDHB12, PCDHB13, PCDHB14, PCDHB15, PCDHB16, PCDHB17, PCDHB18, PCDHB2, PCDHB3, PCDHB4, PCDHBS, PCDHB6, PCDHB7, PCDHB8, PCDHB9, PCDHGA1, PCDHGA10, PCDHGA11, PCDHGA12, PCDHGA2; PCDHGA3, PCDHGA4, PCDHGAS, PCDHGA6, PCDHGA7, PCDHGA8, PCDHGA9, PCDHGB1, PCDHGB2, PCDHGB3, PCDHGB4, PCDHGB5, PCDHGB6, PCDHGB7, PCDHGC3, PCDHGC4, PCDHGC5, CDH9 (cadherin 9, type 2 (T1-cadherin)), CDH10 (cadherin 10, type 2 (T2-cadherin)), CDHS (VE-cadherin (vascular endothelial)), CDH6 (K-cadherin (kidney)), CDH7 (cadherin 7, type 2), CDH8 (cadherin 8, type 2), CDH11 (OB-cadherin (osteoblast)), CDH13 (T-cadherin-H-cadherin (heart)), CDH15 (M- cadherin (myotubule)), CDH16 (KSP-cadherin), CDH17 (LI cadherin (liver-intestine)), CDH18 (cadherin 18, type 2), CDH19 (cadherin 19, type 2), CDH20 (cadherin 20, type 2), CDH23 (cadherin 23, (neurosensory epithelium)), CDH10, CDH11, CDH13, CDH15, CDH16, CDH17, CDH18, CDH19, CDH20, CDH22, CDH23, CDH24, CDH26, CDH28, CDH4, CDH5, CDH6, CDH7, CDH8, CDH9, CELSR1, CELSR2, CELSR3, CLSTN1, CLSTN2, CLSTN3, DCHS1, DCHS2, LOC389118, PCLKC, RESDA1, RET ECAD (CDH1) SNAI1/SNAIL, ZEHX1B/SIP1, downregulators SNAI2/SLUG, TWIST1, DeltaEF1 ECAD AML1, p300, HNF3 upregulators ECAD interacting ACADVL, ACTG1, ACTN1, ACTN4, ACTR3, proteins ADAM10, ADAM9, AJAP1, ANAPC1, ANAPC11, ANAPC4, ANAPC7, ANK2, ANP32B, APC2, ARHGAP32, ARPC2, ARVCF, BOC, C1QBP, CA9, CASP3, CASP8, CAV1, CBLL1, CCNB1, CCND1, CCT6A, CDC16, CDC23, CDC26, CDC27, CDC42, CDH2, CDH3, CDK5R1, CDON, CDR2, CFTR, CREBBP, CSE1L, CSNK2A1, CTNNA1, CTNNB1, CTNND1, CTNND2, DNAJA1, DRG1, EGFR, EP300, ERBB2, ERBB2IP, ERG, EZR, FER, FGFR1, FOXM1, FRMD5, FYN, GBAS, GNA12, GNA13, GNB2L1, GSK3B, HDAC1, HDAC2, HSP90AA1, HSPA1A, HSPA1B, HSPD1, IGHA1, IQGAP1, IRS1, ITGAE, ITGB7, JUP, KIFC3, KLRG1, KRT1, KRT9, LIMA1, LMNA, MAD2L2, MAGI1, MAK, MDM2, MET, MYO6, MYO7A, NDRG1, NEDD9, NIPSNAP1, NKD2, PHLPP1, PIP5K1C, PKD1, PKP4, PLEKHA7, POLR2E, PPP1CA, PRKD1, PSEN1, PTPN1, PTPN14, PTPRF, PTPRM, PTPRQ, PTTG1, PVR, PVRL1, RAB8B, RRM2, SCRIB, SET, SIX1, SKI, SKP2, SRC, TACC3, TAS2R13, TGM2, TJP1, TK1, TNS3, TTK, UBC, USP9X, VCL, VEZT, XRCC5, YAP1, YES1, ZC3HC1 Epithelial- SERPINA3, ACTN1, AGR2, AKAP12, ALCAM, mesenchymal AP1M2, AXL, BSPRY, CCL2, CDH1, transition (EMT) CDH2, CEP170, CLDN3, CLDN4, CNN3, CYP4X1, DNMT3A, DSG3, DSP, EFNB2, EHF, ELF3, ELF5, ERBB3, ETV5, FLRT3, FOSB, FOSL1, FOXC1, FX YD 5, GPDIL, HMGA1, HMGA2, HOPX, IF116, IGFBP2, IHH, IKBIP, IL-11, IL-18, IL6, IL8, ITGA5, ITGB3, LAMB1, LCN2, MAP7, MB, MMP7, MMP9, MPZL2, MSLN, MTA3, MTSS1, OCLN, PCOLCE2, PECAM1, PLAUR, PLXNB1, PPL, PPP1R9A, RASSF8, SCNN1A, SERPINB2, SERPINE1, SFRP1, SH3YL1, SLC27A2, SMAD7, SNAI1, SNAI2, SPARC, SPDEF, SRPX, STAT5A, TBX2, TJP3, TMEM125, TMEM45B, TWIST1, VCAN, VIM, VWF, XBP1, YBX1, ZBTB10, ZEB1, ZEB2

In various embodiments of the invention, the biomarkers or biosignature comprising one or more biomarkers used to detect or assess any of the conditions or diseases disclosed herein can comprise one or more biomarkers in one of several different categories of markers, wherein the categories include one or more of: 1) disease specific biomarkers; 2) cell- or tissue-specific biomarkers; 3) vesicle-specific markers (e.g., general vesicle biomarkers); 4. angiogenesis-specific biomarkers; and 5) immunomodulatory biomarkers. Examples of all such markers are disclosed herein and known to a person having ordinary skill in the art. Furthermore, a biomarker known in the art that is characterized to have a role in a particular disease or condition can be adapted for use as a target in compositions and methods of the invention. In further embodiments, such biomarkers that are associated with vesicles can be all vesicle surface markers, or a combination of vesicle surface markers and vesicle payload markers (i.e., molecules enclosed by a vesicle). The biomarkers assessed can be from a combination of sources. For example, a disease or disorder may be detected or characterized by assessing a combination of proteins, nucleic acids, vesicles, circulating biomarkers, biomarkers from a tissue sample, and the like. In addition, as noted herein, the biological sample assessed can be any biological fluid, or can comprise individual components present within such biological fluid (e.g., vesicles, nucleic acids, proteins, or complexes thereof).

Therapeutics

Aptamer-Toxin Conjugates as a Cancer Therapeutic

Extensive previous work has developed the concept of antibody-toxin conjugates (“immunoconjugates”) as potential therapies for a range of indications, mostly directed at the treatment of cancer with a primary focus on hematological tumors. A variety of different payloads for targeted delivery have been tested in pre-clinical and clinical studies, including protein toxins, high potency small molecule cytotoxics, radioisotopes, and liposome-encapsulated drugs. While these efforts have successfully yielded three FDA-approved therapies for hematological tumors, immunoconjugates as a class (especially for solid tumors) have historically yielded disappointing results that have been attributable to multiple different properties of antibodies, including tendencies to develop neutralizing antibody responses to non-humanized antibodies, limited penetration in solid tumors, loss of target binding affinity as a result of toxin conjugation, and imbalances between antibody half-life and toxin conjugate half-life that limit the overall therapeutic index (reviewed by Reff and Heard, Critical Reviews in Oncology/Hematology, 40 (2001):25-35).

Aptamers are functionally similar to antibodies, except their absorption, distribution, metabolism, and excretion (“ADME”) properties are intrinsically different and they generally lack many of the immune effector functions generally associated with antibodies (e.g., antibody-dependent cellular cytotoxicity, complement-dependent cytotoxicity). In comparing many of the properties of aptamers and antibodies previously described, several factors suggest that toxin-delivery via aptamers offers several concrete advantages over delivery with antibodies, ultimately affording them better potential as therapeutics. Several examples of the advantages of toxin-delivery via aptamers over antibodies are as follows:

1) Aptamer-toxin conjugates are entirely chemically synthesized. Chemical synthesis provides more control over the nature of the conjugate. For example, the stoichiometry (ratio of toxins per aptamer) and site of attachment can be precisely defined. Different linker chemistries can be readily tested. The reversibility of aptamer folding means that loss of activity during conjugation is unlikely and provides more flexibility in adjusting conjugation conditions to maximize yields.

2) Smaller size allows better tumor penetration. Poor penetration of antibodies into solid tumors is often cited as a factor limiting the efficacy of conjugate approaches. See Colcher, D., Goel, A., Pavlinkova, G., Beresford, G., Booth, B., Batra, S. K. (1999) “Effects of genetic engineering on the pharmacokinetics of antibodies,” Q. J. Nucl. Med., 43: 132-139. Studies comparing the properties of unPEGylated anti-tenascin C aptamers with corresponding antibodies demonstrate efficient uptake into tumors (as defined by the tumor:blood ratio) and evidence that aptamer localized to the tumor is unexpectedly long-lived (t_(1/2)>12 hours) (Hicke, B. J Stephens, A. W., “Escort aptamers: a delivery service for diagnosis and therapy”, J. Clin. Invest., 106:923-928 (2000)).

3) Tunable P K. Aptamer half-life/metabolism can be easily tuned to match properties of payload, optimizing the ability to deliver toxin to the tumor while minimizing systemic exposure. Appropriate modifications to the aptamer backbone and addition of high molecular weight PEGs should make it possible to match the half-life of the aptamer to the intrinsic half-life of the conjugated toxin/linker, minimizing systemic exposure to non-functional toxin-bearing metabolites (expected if t_(1/2)(aptamer)<<t_(1/2)(toxin)) and reducing the likelihood that persisting unconjugated aptamer will functionally block uptake of conjugated aptamer (expected if t_(1/2)(aptamer)>>t_(1/2)(toxin)).

4) Relatively low material requirements. It is likely that dosing levels will be limited by toxicity intrinsic to the cytotoxic payload. As such, a single course of treatment will likely entail relatively small (<100 mg) quantities of aptamer, reducing the likelihood that the cost of oligonucleotide synthesis will be a barrier for aptamer-based therapies.

5) Parenteral administration is preferred for this indication. There will be no special need to develop alternative formulations to drive patient/physician acceptance.

Aptamer Identification Methods

Nucleic acid sequences fold into secondary and tertiary motifs particular to their nucleotide sequence. These motifs position the positive and negative charges on the nucleic acid sequences in locations that enable the sequences to bind to specific locations on target molecules, e.g., proteins and other amino acid sequences. These binding sequences are known in the field as aptamers. Due to the trillions of possible unique nucleotide sequences in even a relatively short stretch of nucleotides (e.g., 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, or 40), a large variety of motifs can be generated, resulting in aptamers for almost any desired protein or other target.

Aptamers are created by randomly generating oligonucleotides of a specific length, typically 20-40 base pairs long, e.g., 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, or 40 base pairs. These random oligonucleotides are then incubated with the protein target of interest. After several wash steps, the oligonucleotides that bind to the target are collected and amplified. The amplified aptamers are then added to the target and the process is repeated, often 15-20 times. A common version of this process known to those of skill in the art as the SELEX method.

The end result comprises one or more aptamer with high affinity to the target. The invention provides further processing of such resulting aptamers that can be use to provide desirable characteristics. The invention also provides use of the aptamers to detect a target of interest, e.g., to detect a biological entity such as a protein, nucleic acid, or microvesicle. In an aspect, the aptamers of the invention bind to functional groups of interest. In an embodiment, the invention provides aptamers that bind to carboxyl groups. The methods are described in more detail below and further in the Examples.

Motif Analysis

In most aptamer experiments, multiple aptamer sequences are identified that bind to the target. These aptamers will have various binding affinities. It can be time consuming and laborious to generate quantities of these many aptamers sufficient to assess the affinities of each. To identify large numbers of aptamers with the highest affinities without physically screening large subsets, the invention provides a method comprising the analysis of the two dimensional structure of one or more high affinity aptamers to the target of interest. In an embodiment, the method comprises screening the database for aptamers that have similar two-dimensional structures, or motifs, but not necessarily similar primary sequences. In an embodiment, the method comprises identifying a high affinity aptamer using traditional methods such as disclosed herein or known in the art (e.g. surface plasmon resonance binding assay), approximating the two-dimensional structure of the high affinity aptamer, and identifying aptamers from a pool of sequences that are predicted to have a similar two-dimensional structure to the high affinity aptamer. The method thereby provides a pool of candidates that also bind the target of interest. The two-dimensional structure of an oligo can be predicting using methods known in the art, e.g., via a commercially available software program such as Vienna or mFold. The pool of sequences can be sequenced from a pool of randomly generated aptamer candidates using a high-throughput sequencing platform, such as the Ion Torrent platform from Life Technologies or Truseq platform from Illumina Corporation. Identifying aptamers from a pool of sequences that are predicted to have a similar two-dimensional structure to the high affinity aptamer may comprise loading the resulting sequences into the software program of choice to identify members of the pool of sequences with similar two-dimensional structures as the high affinity aptamer. The affinities of the pool of sequences can then be determined in situ, e.g., surface plasmon resonance binding assay or the like.

Binding Agent Selection

In an aspect, the invention provides a method to identify a binding agent that is specific for or binds to a target molecule present in a sample, or a plurality of binding agents that bind to a plurality of target molecules present in a sample. The binding agent in the context of any of the embodiments herein can be any molecular that is capable of binding to a desired target molecule. Examples of such binding agents are disclosed herein. Binding agents can be used in various biological assays, e.g., to detect the presence or level of a biological entity in a biological sample. The invention provides methods to identify binding agents that differentially detect two biological samples, e.g., normal versus diseased samples. In various embodiments of the invention, the binding agents comprise aptamers. The targets may comprise microvesicles or components thereof, e.g., microvesicle surface antigens.

In an aspect, the invention provides a method of identifying one or more binding agent comprising: (a) providing a pool of candidate binding agents; (b) contacting a first one or more biological sample with an aliquot of the pool provided in step (a); (c) identifying a first subpool of candidate binding agents that bound one or more biological component of the first one or more biological sample in step (b); (d) contacting a second one or more biological sample with another aliquot of the pool provided in step (a); (e) identifying a second subpool of candidate binding agents that bound one or more biological component of the second one or more biological sample in step (d); and (f) comparing the members of the first and second subpools of candidate binding agents to identify one or more member of a pool that is overrepresented in one subpool versus the other subpool, thereby identifying the one or more binding agent.

FIGS. 2A-B illustrates the method of identifying one or more binding agent, e.g., an aptamer, from a pool of candidate binding agents. The method is used to select one or more binding agent from the pool that is specific for one or more biological entity of interest. As shown in FIG. 2A, a pool of candidate binding agents is provided 200. The pool can comprise any type of binding agent disclosed herein or known in the art for which a pool of potential agents is available. Various aliquots of the pool are contacted with a first sample 201 and a second sample 203. Contacting each of the first sample or second sample may comprise contacting one or more (1 . . . n) samples. For example, 201 may comprise contacting 50 samples and 203 may comprise contacting 50 samples. After the contacting steps, binding agents that recognize one or more component of the input samples are identified (202, 204). For example, consider that the input sample comprises one or microvesicle. The pool of candidate binding agents is contacted with the input sample, one or more microvesicles are recovered from the input sample, and one or more binding agents from the pool that are bound to the one or more recovered microvesicle are identified. Methods of identifying are disclosed herein or known in the art, e.g., sequencing. The identified binding agents that bound the input samples are compared 205. Binding agents that bound in higher levels to to one sample versus the other comprise potentially useful binding agents that can distinguish between the first and second input samples. The one or more binding agent are indicated as recognizing biological entities such as biomarkers in the samples that are differentially present or differentially expressed between the groups of samples. As shown in FIG. 2B, one or more recognize only one of the first and second samples but not the other 206 optionally are further filtered as desired (207, 208, 209). Any number of filters (1 . . . n) can be applied. As described further below, exemplary filters that can be applied to the pools of binding agents identified in 206 include analysis of stability 207, analysis of secondary structure 208, and binding analysis 208 using laboratory methods (immunoassay, Biacore, etc). The filters can also be applied in an iterative manner as desired, e.g., stability 207 then structure 208 then binding analysis 209. Filtering provides a reduced set of one or more binding agent 210. If desired, e.g., to further reduce the number of members of a pool of binding agents, the one or more binding agent identified in 206 or 210 can be used as input to the method 200.

FIG. 2C presents an illustration of the identified one or more binding agents relative to the input samples. For purposes of illustration, three samples are represented by the circles (Sample 1, circle 211; Sample 2, circle 212; Sample 3, circle 213). Each circle represents a subpool of binding agents that bind to one or more component in the respective sample. Regions R1-R7 each represent an area of overlap or non-overlap in a portion of a subpool of binding agents. Consider a scenario wherein the first one or more biological sample consists of Sample 1 and the second one or more biological sample consists of Sample 2. In such case, R1+R5 (i.e, the addition of region R1 and region R5) represents a subpool of binding agents that are specific for Sample 1 but not Sample 2, R3+R6 represents a subpool of binding agents that are specific for Sample 2 but not Sample 3, and R2+R4 represents a subpool of common binding agents to both samples. According to the methods of the invention, both R1+R5 and R3+R6 may comprise the identified one or more binding agent. Now consider a scenario wherein the first one or more biological sample still consists of Sample 1 and the second one or more biological sample consists of both Sample 2 and Sample 3 (i.e., “Sample 2+Sample 3”). In such case, R1 represents a subpool of binding agents that are specific for Sample 1 but not Sample 2+Sample 3, R3+R6+R7 represent a subpool of binding agents that are specific for Sample 2+Sample 3 but not Sample 1, and R2+R4+R5 represents a subpool of binding agents that are common to both Sample 1 and Sample 2+Sample 3. According to the methods of the invention, both regions R1 and R3+R6+R7 may comprise the identified one or more binding agent. At the same time, Samples 2 and 3 can also be compared and binding agent specific to either one but not the other are identified as described above. It will be appreciated that these scenarios can be extended such that the first one or more biological sample consists of any appropriate number of samples (1 . . . n) and the second one or more biological sample consists of any appropriate number of samples (1 . . . n). The sample groups can comprise any desired sample groupings as described further below.

The one or more binding agent may comprise a binding agent disclosed herein or known in the art. For example, the one or more binding may be a nucleic acid, DNA molecule, RNA molecule, antibody, antibody fragment, aptamer, peptoid, zDNA, peptide nucleic acid (PNA), locked nucleic acid (LNA), lectin, polypeptide, peptide, dendrimer, membrane protein labeling agent, chemical compound, a derivative of any thereof, or a combination thereof. In an embodiment, the one or more binding agent comprises an aptamer. The pool of candidate binding agents may comprise at least 10, 10², 10³, 10⁴, 10⁵, 10⁶, 10⁷, 10⁸, 10⁹, 10¹⁰, 10¹¹, 10¹², 10¹³, 10¹⁴, 10¹⁵, 10¹⁶, 10¹⁷, 10¹⁸, 10¹⁹ or at least 10²⁰ unique members. For example, the pool of candidate binding agents may comprise a pool of aptamers comprising at least 10, 10², 10³, 10⁴, 10⁵, 10⁶, 10⁷, 10⁸, 10⁹, 10¹⁰, 10¹¹, 10¹², 10¹³, 10¹⁴, 10¹⁵, 10¹⁶, 10¹⁷, 10¹⁸, 10¹⁹ or at least 10²⁰ unique nucleic acids.

The method of the invention may comprise contacting a plurality of samples with aliquots of the pool of candidate binding agents. A plurality of first biological samples is separately contacted with an aliquot of the pool in step (b) and/or a plurality of second biological samples is separately contacted with an aliquot of the pool in step (d). The plurality may comprise at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or at least 100 samples. For example, 50 samples of each of the first and second biological sample types can be contacted with an aliquot of the pool of candidate binding agents. When a plurality of samples is used, the first and/or second subpools can comprise a mixture of all members of the pool of candidate binding agents that bound to any of the appropriate contacted samples.

In some embodiments, the contacting and optionally identifying steps are repeated at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or at least 20 times before comparing members of the first and second subpools. Multiple rounds may provide improved stringency of selection of binding agents to the samples of interest.

The method of the invention can identity one or more binding agent that differentiate two different biological samples. For example, one of skill will appreciate that a binding agent that recognizes one sample or group of samples as compared to another sample or group of samples can be used in various assays to distinguish the samples. In an embodiment, the first one or more biological sample comprises a diseased sample. In embodiments, the second one or more biological sample comprises a control sample, e.g., a non-diseased sample. Each of the first one or more biological samples can comprise a same disease, wherein the scope of disease can be selected. In a non-limiting example, the disease could be a cancer wherein a variety of different cancers are represented in the the first one or more biological sample. By comparing to a normal control, the method can identify binding agents that distinguish all cancers from normals. In another non-limiting example, the disease could be a type of cancer, e.g., a prostate or breast cancer, wherein a variety of samples of the prostate or breast cancer are represented in the the first one or more biological sample. By comparing to a normal control, the method can identify binding agents that distinguish prostate cancers from normals. In still another non-limiting example, the disease could be a subtype of cancer, e.g., a ER+/PR+ breast cancer, wherein a variety of samples of the ER+/PR+ breast cancer cancer are represented in the the first one or more biological sample. By comparing to a normal control, the method can identify binding agents that distinguish ER+/PR+ breast cancer from normals. In still another example, the first one or more biological sample can comprise diseased samples from a patient, e.g., tumor samples, and the the first one or more biological sample can comprise non-diseased samples from the same patient, e.g., normal adjacent tissue.

One of skill will appreciate that the first and second samples can be chosen to provide binding agents that distinguish any desired sample groupings. In an embodiment, the first one or more biological sample comprises the same disease as the second one or more biological sample. In such cases, the first and second samples can be chosen such that the disease in the sample or sample groups differs in one of more of clinical stage, pathologic stage, aggressiveness, growth rate, receptor status, prior treatment, response to a same to treatment, and response to different treatments. Thus, the method of the invention can be used to identify distinguish samples along the lines of any of these characteristics.

The method can be used to identify binding agents specific for any appropriate and desired disease, such as those disclosed herein or known in the art. In some embodiments, the disease comprises a cancer. In embodiments, the cancer comprises an acute lymphoblastic leukemia; acute myeloid leukemia; adrenocortical carcinoma; AIDS-related cancers; AIDS-related lymphoma; anal cancer; appendix cancer; astrocytomas; atypical teratoid/rhabdoid tumor; basal cell carcinoma; bladder cancer; brain stem glioma; brain tumor (including brain stem glioma, central nervous system atypical teratoid/rhabdoid tumor, central nervous system embryonal tumors, astrocytomas, craniopharyngioma, ependymoblastoma, ependymoma, medulloblastoma, medulloepithelioma, pineal parenchymal tumors of intermediate differentiation, supratentorial primitive neuroectodermal tumors and pineoblastoma); breast cancer; bronchial tumors; Burkitt lymphoma; cancer of unknown primary site; carcinoid tumor; carcinoma of unknown primary site; central nervous system atypical teratoid/rhabdoid tumor; central nervous system embryonal tumors; cervical cancer; childhood cancers; chordoma; chronic lymphocytic leukemia; chronic myelogenous leukemia; chronic myeloproliferative disorders; colon cancer; colorectal cancer; craniopharyngioma; cutaneous T-cell lymphoma; endocrine pancreas islet cell tumors; endometrial cancer; ependymoblastoma; ependymoma; esophageal cancer; esthesioneuroblastoma; Ewing sarcoma; extracranial germ cell tumor; extragonadal germ cell tumor; extrahepatic bile duct cancer; gallbladder cancer; gastric (stomach) cancer; gastrointestinal carcinoid tumor; gastrointestinal stromal cell tumor; gastrointestinal stromal tumor (GIST); gestational trophoblastic tumor; glioma; hairy cell leukemia; head and neck cancer; heart cancer; Hodgkin lymphoma; hypopharyngeal cancer; intraocular melanoma; islet cell tumors; Kaposi sarcoma; kidney cancer; Langerhans cell histiocytosis; laryngeal cancer; lip cancer; liver cancer; malignant fibrous histiocytoma bone cancer; medulloblastoma; medulloepithelioma; melanoma; Merkel cell carcinoma; Merkel cell skin carcinoma; mesothelioma; metastatic squamous neck cancer with occult primary; mouth cancer; multiple endocrine neoplasia syndromes; multiple myeloma; multiple myeloma/plasma cell neoplasm; mycosis fungoides; myelodysplastic syndromes; myeloproliferative neoplasms; nasal cavity cancer; nasopharyngeal cancer; neuroblastoma; Non-Hodgkin lymphoma; nonmelanoma skin cancer; non-small cell lung cancer; oral cancer; oral cavity cancer; oropharyngeal cancer; osteosarcoma; other brain and spinal cord tumors; ovarian cancer; ovarian epithelial cancer; ovarian germ cell tumor; ovarian low malignant potential tumor; pancreatic cancer; papillomatosis; paranasal sinus cancer; parathyroid cancer; pelvic cancer; penile cancer; pharyngeal cancer; pineal parenchymal tumors of intermediate differentiation; pineoblastoma; pituitary tumor; plasma cell neoplasm/multiple myeloma; pleuropulmonary blastoma; primary central nervous system (CNS) lymphoma; primary hepatocellular liver cancer; prostate cancer; rectal cancer; renal cancer; renal cell (kidney) cancer; renal cell cancer; respiratory tract cancer; retinoblastoma; rhabdomyosarcoma; salivary gland cancer; Sézary syndrome; small cell lung cancer; small intestine cancer; soft tissue sarcoma; squamous cell carcinoma; squamous neck cancer; stomach (gastric) cancer; supratentorial primitive neuroectodermal tumors; T-cell lymphoma; testicular cancer; throat cancer; thymic carcinoma; thymoma; thyroid cancer; transitional cell cancer; transitional cell cancer of the renal pelvis and ureter; trophoblastic tumor; ureter cancer; urethral cancer; uterine cancer; uterine sarcoma; vaginal cancer; vulvar cancer; Waldenström macroglobulinemia; or Wilm's tumor. The disease can be a prostate cancer, a lung cancer, a breast cancer, a brain cancer, an ovarian cancer, a colorectal cancer, or a melanoma.

The biological samples used by the methods of the invention can comprise any useful sample of interest. In some embodiments, the samples comprise a tissue sample or cell culture sample. For example, the sample could be a solid tumor sample or from a cancer cell culture. The biological sample may also comprise a bodily fluid. Non-limiting examples of useful bodily fluids comprise peripheral blood, sera, plasma, ascites, urine, cerebrospinal fluid (CSF), sputum, saliva, bone marrow, synovial fluid, aqueous humor, amniotic fluid, cerumen, breast milk, broncheoalveolar lavage fluid, semen, prostatic fluid, cowper's fluid or pre-ejaculatory fluid, female ejaculate, sweat, fecal matter, hair, tears, cyst fluid, pleural and peritoneal fluid, pericardial fluid, lymph, chyme, chyle, bile, interstitial fluid, menses, pus, sebum, vomit, vaginal secretions, mucosal secretion, stool water, pancreatic juice, lavage fluids from sinus cavities, bronchopulmonary aspirates, blastocyl cavity fluid, umbilical cord blood, or a derivative of any thereof. In various embodiments, the biological sample comprises peripheral blood, plasma, serum or a derivative of any thereof.

The biological sample of these or other origin may comprise a heterogeneous microvesicle population or a homogeneous microvesicle population. As used in the context of microvesicles, the term “heterogenous” means the microvesicle population may comprise microvesicles that are of different cellular or tissue origin, are produced through different biological or cellular mechanisms, and/or comprise microvesicles of different sizes as discussed herein. As used in the context of microvesicles, the term “homogeneous” means without limitation, that the microvesicle population comprise microvesicles that are of the same cellular or tissue origin, are produced through the same biological or cellular mechanisms and/or comprise microvesicles of the same size range as discussed herein. In a non-limiting example, a homogeneous microvesicle population can be obtained from a heterogeneous microvesicle population by subjecting the heterogeneous microvesicle population to affinity isolation or size exclusion methodology.

The one or more component of the biological sample can be any appropriate entity that can be detected when recognized by a binding agent (e.g., polypeptides, peptide, nucleic acid molecules, carbodyhrates, lipids, etc.). In an embodiment, the one or more component of the biological sample comprises a protein or polypeptide. As used herein, “protein,” “polypeptide” and “peptide” are used interchangeably unless stated otherwise. The one or more component of the biological sample may comprise one or more microvesicle. The one or more component of the biological sample can be a nucleic acid, including DNA, RNA, and various subspecies of any thereof as disclosed herein or known in the art. The one or more component of the biological sample can comprise a lipid. The one or more component of the biological sample can comprise a carbohydrate. The one or more component of the biological sample can also be a complex, e.g., a complex comprising protein, nucleic acids, lipids and/or carbohydrates. In some embodiments, the one or more component of the biological sample comprises a microvesicle. In such cases, the binding agent may recognize a microvesicle surface antigen, e.g., a surface protein. General microvesicle surface antigens include tetraspanin, CD9, CD63, CD81, CD63, CD9, CD81, CD82, CD37, CD53, Rab-5b, Annexin V, and MFG-E8. Additional general microvesicle surface antigens are provided in Table 2 herein. The binding agent can also be directed to a biological entity within a microvesicle, e.g., as referred to herein as microvesicle “payload.”

The microvesicle surface antigen can also be a biomarker of a disease or disorder. In such cases, the binding agent may be used to provide a diagnosis, prognosis or theranosis of the disease or disorder. For example, the one or more protein may comprise one or more of PSMA, PCSA, B7H3, EpCam, ADAM-10, BCNP, EGFR, IL1B, KLK2, MMP7, p53, PBP, SERPINB3, SPDEF, SSX2, and SSX4. These markers can be used detect a prostate cancer. Additional microvesicle surface antigens are provided in Tables 2-3 herein.

Because the binding agents are identified based on their ability to bind a component of a sample without requiring prior knowledge of the component, one of skill will appreciate that the method will often identify binding agents to novel biomarkers. In this context, a “novel biomarker” may comprise a previously unknown entity, or may be a previously known entity that is wholly or partially unknown to differentiate the input samples. The method may also identify one or more binding agents to a selection of known biomarkers and a selection of novel biomarkers. As a non-limiting example, consider that the input samples comprise a group of prostate cancer samples and a group of normal control samples (i.e., no prostate cancer). The method may identify binding agents to known prostate cancer protein biomarkers (e.g., PSA, PCSA, KLK2, PBP) and/or to one or protein previously known as a useful biomarker for detecting prostate cancer.

The identifying in step (c) and/or step (e) comprise identifying the candidate binding agents. In various embodiments, identifying comprises sequencing the candidate binding agents that bound the one or more biological components. One of skill will appreciate that the technique for identifying the the one or more binding agent will depend on the type of binding agent. For example, when the one or more binding agent comprises a protein, identifying the target may comprise use of mass spectrometry (MS), peptide mass fingerprinting (PMF; protein fingerprinting), sequencing, N-terminal amino acid analysis, C-terminal amino acid analysis, Edman degradation, chromatography, electrophoresis, two-dimensional gel electrophoresis (2D gel), antibody array, and immunoassay. Nucleic acids can be identified by sequencing, e.g., Sanger sequencing, high throughput sequencing, Next generation sequencing, pyrosequencing, or other such methods known in the art.

When the pool of candidate binding agents comprises nucleic acids, e.g., aptamers, high throughput can be a preferred technique to identify the binding agents. A sequence analysis apparatus or sequence analysis component(s) includes an apparatus, and one or more components used in conjunction with such apparatus, that can be used by a person of ordinary skill to determine a nucleotide sequence resulting from processes described herein or known in the art (e.g., linear and/or exponential amplification products). Examples of sequencing platforms include, without limitation, the 454 platform (Roche) (Margulies, M. et al. 2005 Nature 437, 376-380), Illumina Genomic Analyzer (or Solexa platform) or SOLID System (Applied Biosystems; see PCT patent application publications WO 06/084132 entitled “Reagents, Methods, and Libraries For Bead-Based Sequencing” and WO07/121,489 entitled “Reagents, Methods, and Libraries for Gel-Free Bead-Based Sequencing”), the Helicos True Single Molecule DNA sequencing technology (Harris T D et al. 2008 Science, 320, 106-109), the single molecule, real-time (SMRT™) technology of Pacific Biosciences, and nanopore sequencing (Soni G V and Meller A. 2007 Clin Chem 53: 1996-2001), Ion semiconductor sequencing (Ion Torrent Systems, Inc, San Francisco, Calif.), or DNA nanoball sequencing (Complete Genomics, Mountain View, Calif.), VisiGen Biotechnologies approach (Invitrogen) and polony sequencing. Such platforms allow sequencing of many nucleic acid molecules isolated from a specimen at high orders of multiplexing in a parallel manner (Dear Brief Funct Genomic Proteomic 2003; 1: 397-416; Haimovich, Methods, challenges, and promise of next-generation sequencing in cancer biology. Yale J Biol Med. 2011 December; 84(4):439-46). These non-Sanger-based sequencing technologies are sometimes referred to as massively parallel sequencing, NextGen sequencing, NGS, next-generation sequencing, next generation sequencing, and variations thereof. Typically they allow much higher throughput than the traditional Sanger approach. See Schuster, Next-generation sequencing transforms today's biology, Nature Methods 5:16-18 (2008); Metzker, Sequencing technologies—the next generation. Nat Rev Genet. 2010 January; 11(1):31-46. These platforms can allow sequencing of clonally expanded or non-amplified single molecules of nucleic acid fragments. Certain platforms involve, for example, sequencing by ligation of dye-modified probes (including cyclic ligation and cleavage), pyrosequencing, and single-molecule sequencing. Nucleotide sequence species, amplification nucleic acid species and detectable products generated there from can be analyzed by such sequence analysis platforms. Next-generation sequencing can be used in the methods of the invention, e.g., to identify binding agents or the targets thereof. In one embodiment of the methods of the invention, the candidate binding agents are assessed using commercially available Next Generation sequencing systems, e.g., using a TruSeq/MiSeq system offered by Illumina Corporation (Austin, Tex.) or an Ion Torrent system from Life Technologies (Carlsbad, Calif.).

In various embodiments of the methods of the invention, comparing the members of the first and second subpools in step (f) comprises comparing the sequences of the candidate binding agents identified in step (c) and/or step (e). Bioinformatics analysis methods known in the art can be used to compare the sequences. E.g., various bioinformatics tools are known in the art that can compare groups of sequences.

A threshold can be set for determining whether the one or more member of a pool is overrepresented in one subpool versus the other subpool in step (f). One of skill will appreciate that the threshold can depend on downstream uses for the identified one or more binding agent. For example, consider that the identified one or more binding agent will be used in an assay to differentiate biological samples, e.g., to differentiate between one or more sample that is similar to or suspected to be similar to the first one or more biological sample, and one or more sample that is similar to or suspected to be similar to the second one or more biological sample. Illustrative sample groupings are provided above. In such a scenario, the degree to which the one or more member of a pool that is overrepresented in one subpool versus the other subpool can be set be such that the identified one or more binding agent may comprise a useful tool for carrying out said assay. In various embodiments, the threshold is set such that the identified one or more binding agent is overrepresented in one subpool versus the other by at least 1.1-fold, 1.2-fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold, 1.7-fold, 1.8-fold, 1.9-fold, 2-fold, 2.5-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 20-fold, 30-fold, 40-fold, 50-fold, 60-fold, 70-fold, 80-fold, 90-fold, 100-fold, 200-fold, 300-fold, 400-fold, 500-fold, 600-fold, 700-fold, 800-fold, 900-fold, 10³-fold, 10⁴-fold, 10⁵-fold, 10⁶-fold, 10⁷-fold, 10⁸-fold, 10⁹-fold, 10¹⁰-fold, 10¹¹-fold, 10¹²-fold, 10¹³-fold, 10¹⁴-fold, 10¹⁵-fold, 10¹⁶-fold, 10¹⁷-fold, 10¹⁸-fold, 10¹⁹-fold or at least 10²⁰-fold. In an embodiment, the one or more binding agent identified in step (f) is wholly found in the overrepresented subpool and absent in the other subpool.

The one or more binding agent identified by the methods of the invention can be further filtered to reduce the number of members of the pool as desired. For example, filtering a pool or subpool can comprise applying a method to reduce the number of members thereof by at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 99.1%, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9%, 99.99% or by at least 99.999%. The techniques used to filter a pool or subpool can depend on the type of binding agent. For example, consider a pool of candidate aptamers. In such cases, filtering may comprise calculating a stability of the one or more binding agent, identifying a secondary structure of the one or more binding agent, and/or separately contacting each of the one or more binding agent with a biological sample. In the latter method, the binding agent can be used in an affinity assay to directly detect binding events to the sample component. During filtering, binding agents with desired characteristics may be preferentially retained. For example, aptamers with greater estimated stability may be retained over aptamers with lower estimated stability. Similarly, a subset from a group of aptamers having common secondary structure motifs may be preferentially retained. Finally, aptamers showing high affinity for the desired target and/or low cross reactivity to non-desired targets may be preferentially retained.

One of skill will appreciate that the methods of the invention and the various means of additional filtering can be applied iteratively and in any order to identify one or more binding agent of interest. Using these methods, down to a single binding agent can be obtained from a large starting pool of candidate binding agents, wherein the single binding agent has optimized ability to detect a component of a biological sample.

In one embodiment, the method of the invention further comprises identifying the biological component recognized by the one or more identified binding agent. One of skill will appreciate that the technique for identifying the the biological component will depend on the type of biological component. For example, when the component comprises a protein, identifying the target may comprise use of mass spectrometry (MS), peptide mass fingerprinting (PMF; protein fingerprinting), sequencing, N-terminal amino acid analysis, C-terminal amino acid analysis, Edman degradation, chromatography, electrophoresis, two-dimensional gel electrophoresis (2D gel), antibody array, and immunoassay. Nucleic acids can be identified by sequencing, e.g., Sanger sequencing, Next generation sequencing, pyrosequencing, or other such methods known in the art.

In another aspect, the invention provides a method of detecting a presence or level of a biological entity, comprising contacting a test biological sample with one or more binding agent identified by the methods above. The binding agents can be used in any appropriate affinity technique such as described herein or known in the art to either capture and/or detect the target of the binding agent. Such techniques include without limitation techniques shown in FIG. 1, affinity selection, immunodetection, bead assays, well assays, microarrays, immunprecipitation, ELISA, flow cytometry, variations of any thereof, and the like. The detected presence or level of the biological entity recognized by the one or more binding agent can be compared to the detected presence or level of the biological entity in one or more reference sample. In various embodiments of the method, the comparison is used to characterize the input sample. For example, the comparison may provide a diagnosis, prognosis or theranosis of a disease in the test biological sample. One of skill will appreciate that the methods of identifying a binding agent from a pool of provided candidate binding agents can use sample groups based on a characterization of interest to be performed with the one or more identified binding agent. Non-limiting examples of such groups can comprise disease versus normal, aggressive disease versus non-aggressive disease, responders to a drug versus non-responders, etc.

The invention further provides a kit comprising one or more reagent for carrying out the method of the invention, as further described below.

Kits

In an aspect of the invention, a kit or package is provided comprising one or more reagent to carry out the methods of the invention. For example, the reagent can comprise the pool of candidate binding agents provided in the method. The one or more reagent can also comprise a buffer, blocker, enzyme, or combination thereof, used to carry out the methods. The kit can contain instructions to carry out assays using the one or more reagent.

In an embodiment, the kit comprises an aptamer library. The kit can be configured to carry out the methods provided herein. For example, the kit can include a pool of candidate aptamers, a substrate.

The invention further provides a kit configured to carry out an assay using a binding agent identified by the methods of the invention. For example, the kit can contain one or more reagent and instructions for detecting the presence or level of a biological entity in a biological sample. In such cases, the kit can include one or more binding agent to a biological entity of interest. The one or more binding agent can be bound to a substrate.

In an embodiment, the kit comprises a set of aptamers that provide a particular aptamer profile for a biological sample. An aptamer profile can include, without limitation, a profile that can be used to characterize a particular disease or disorder.

REFERENCES

-   Dua P, et al. Patents on SELEX and therapeutic aptamers. Recent Pat     DNA Gene Seq. 2008; 2(3):172-86. -   Zhang Y et. al.., Aptamers selected by cell-SELEX for application in     cancer studies. Bioanalysis. 2010 May; 2(5):907-18. -   Patrick Ruff, et al, Real-Time PCR-Coupled CE-SELEX for DNA Aptamer     Selection. ISRN Molecular Biology, vol. 2012. -   Graham J C and Zarbl H (2012) Use of Cell-SELEX to Generate DNA     Aptamers as Molecular Probes of HPV-Associated Cervical Cancer     Cells. PLoS ONE 7(4). -   Arnold, S, et al. One round of SELEX for the generation of DNA     aptamers directed against KLK6. Biol Chem. 2012 Apr. 1;     393(5):343-53. -   Kellar, K. L., 2003, Applications of multiplexed fluorescent     microsphere-based assays to studies of infectious disease. Journal     of Clinical Ligand Assay, 26:76-86. -   Kellar, K. L. and J. P. Douglass, 2003, Multiplexed     microsphere-based flow cytometric immunoassays for human cytokines.     Journal of Immunological Methods, 279: 277-285. -   Kellar, K. L. and M. A. Iannone, 2002, Multiplexed microsphere-based     flow cytometric assays. Experimental Hematology, 30: 1227-1237. -   Kellar, K. L., R. Kalwar, R., K. A. Dubois, D. Crouse, W. D. Chafin,     and B.-E. Kane, 2001, Multiplexed fluorescent bead-based     immunoassays for quantitation of human cytokines in serum and     culture supernatants. Cytometry, 45: 27-36. -   Martins, T. B, 2002, Development of internal controls for the     Luminex instrument as part of a multiple seven-analyte viral     respiratory antibody profile. Clin Diagn Lab Immunol, 9: 41-45. -   Martins, T. B., 2003, The application of true internal controls to     multiplexed fluorescent immunoassays. Journal of Clinical Ligand     Assay, 26:93-97. -   Martins, T. B., B. M. Pasi, C. M. Litwin, and H. R. Hill, 2004,     Heterophile antibody interference in a multiplexed fluorescent     microsphere immunoassay for quantitation of cytokines in human     serum. Clinical and Diagnostic Laboratory Immunology, 11:325-329. -   Brody et al., Life's Simple Measures: Unlocking the Proteome, J.     Mol. Biol. (2012) 422, 595-606. -   Mehan et al., Highly Multiplexed Proteomic Platform for Biomarker     Discovery, Diagnostics, and Therapeutics, Adv Exp Med Biol. (2013)     734:283-300.

EXAMPLES Example 1 Identification of DNA Oligonucleotides that Bind a Target

The target is affixed to a solid substrate, such as a glass slide or a magnetic bead. For a magnetic bead preparation, beads are incubated with a concentration of target protein ranging from 0.1 to 1 mg/ml. The target protein is conjugated to the beads according to a chemistry provided by the particular bead manufacturer. Typically, this involves coupling via an N-hydroxysuccinimide (NHS) functional group process. Unoccupied NHS groups are rendered inactive following conjugation with the target.

Randomly generated oligonucleotides (oligos) of a certain length, such as 32 base pairs long, are added to a container holding the stabilized target. Each oligo contains 6 thymine nucleotides (a “thymine tail”) at either the 5 or 3 prime end, along with a single molecule of biotin conjugated to the thymine tail. Additional molecules of biotin could be added. Each oligo is also manufactured with a short stretch of nucleotides on each end (5-10 base pairs long) corresponding to amplification primers for PCR (“primer tails”).

The oligonucleotides are incubated with the target at a specified temperature and time in phosphate-buffered saline (PBS) at 37 degrees Celsius in 500 microliter reaction volume.

The target/oligo combination is washed 1-10 times with buffer to remove unbound oligo. The number of washes increases with each repetition of the process (as noted below).

The oligos bound to the target are eluted using a buffer containing a chaotropic agent such as 7 M urea or 1% SDS and collected using the biotin tag. The oligos are amplified using the polymerase chain reaction using primers specific to 5′ and 3′ sequences added to the randomized region of the oligos. The amplified oligos are added to the target again for another round of selection. This process is repeated as necessary to observe binding enrichment.

Example 2 Competitive Assay

The process is performed as in Example 1 above, except that a known ligand to the target, such as an antibody, is used to elute the bound oligo species (as opposed to or in addition to the chaotropic agent). For example, anti-target antibodies are used to elute the aptamers from the target.

Example 3 Screening and Affinity Analysis

Aptamers generated from the binding assays described above are sequenced using a high-throughput sequencing platform, such as the Ion Torrent from Life Technologies:

Library Preparation—Aptamers were pooled after ligating barcodes and adapter sequences (Life Technologies) according to manufacturer protocols. In brief, equimolar pools of the aptamers were made using the following steps: Analyzed an aliquot of each library with a Bioanalyzer™ instrument and Agilent DNA 1000 Kit or Agilent High Sensitivity Kit, as appropriate for the final library concentration. The molar concentration (nmol/L) of each amplicon library was determined using the commercially available software (Agilent).

An equimolar pool of the library was prepared at the highest possible concentration.

The combined concentration of the pooled library stock was calculated.

The template dilution factor of the library pool was determined using the following equation: Template Dilution Factor=(Library pool concentration [pM])/26 pM).

Template Preparation—Using a freshly diluted library, the aptamer pool resulting from binding assays provided above were sequenced using conventional sequencing protocols. High throughput (NextGen) sequencing methods can be used as desired.

A number of aptamers were selected based on direct or competitive assays assessing binding to the target moeity (as described above).

Affinity Measurements—These aptamers were then tested for binding affinity using an in vitro binding platform. SPR can be used for this step, e.g., a Biacore SPR machine using the T200 control software, as follows:

Dilute the antigen to a concentration of 32 nM.

Prepare necessary dilutions for kinetics, starting at 32 nM prepare two-fold dilutions of antigen down to 0.5 nM.

The Biacore 200 control software is programmed with the following conditions: Solution: HBS-EP+Buffer; Number of cycles: 3; Contact time: 120 s; Flow rate: 30 μl/min; Dissociation time: 300 s; Solution: Glycine-HCl pH 2.5; Contact time: 120 s; Flow rate: 20 μl/min; Stabilization period: 0 s. The binding affinities of these aptamers are then measured using the SPR assay above, or an alternate in vitro assay assessing the aptamer for a desired function.

Example 4 Motif Analysis

The process of Example 3 is followed to identity a high affinity aptamer to a target of interest. Once a high affinity aptamer is identified, its sequence is then analyzed using a software program to estimate its two-dimensional folding structure. Well-known sequence alignment programs and algorithms for motif identification can be used to identify sequence motifs and reduce the dimensionality of even large data sets of sequences. Further, software programs such as Vienna and mfold are well-known to those skilled in the art of aptamer selection and can be used to further group sequences based on secondary structure motifs (shared shapes). Shared secondary structure of course, does not guarantee identical three-dimensional structure. Therefore “wet-lab” validation of aptamers is still useful as no one set of in silico tools has yet been able to accurately predict the optimal aptamer among a set of aptamer candidates.

Using the same software, the sequences produced in high-throughput sequencing of a pool of candidate aptamers (produced as described in Example 1 above) are analyzed for structural motifs similar to the high-affinity aptamer. Aptamers with similar motifs are chosen and manufactured using the oligo synthesizer. The affinity of promising candidates is determined using SPR as in Example 3.

Example 5 Selection of Aptamers

Aptamers can be used in various biological assays, including numerous types of assays which rely on a binding agent. For example, aptamers can be used instead of antibodies in immune-based assays. This Example provides an aptamer screening method that identifies aptamers that selectively bind to a component in a first sample or group of samples but not in second sample or group of samples. The assay relies on positive selection to identify aptamers that bind a component of a sample.

Screening experiments are performed using five DNA aptamer library pools with 10¹⁵ sequences each and variable lengths (60, 65, 70, 75, 80-mers). The aptamer libraries are pre-amplified and strand separated so that the forward strand (non-biotinylated) serves as an aptamer. Multiple rounds of positive selection are performed. Before each round, the recovered aptamer products are PCR amplified and strand separated using standard methodology (see Example below).

The aptamer libraries and primers used to amplify the recovered aptamers after each round of selection are shown in Table 4. In the aptamer library sequences, 20N-40N refer to the number of random nucleotides in the library sequence.

TABLE 4 Aptamer Library and PCR Primers SEQ ID Identity Sequence(5′->3′) NO. Forward primer 5′-ATCCAGAGTGACGCAGCA 1 Forward primer 5′-ACTAAGCCACCGTGTCCA 2 Reverse primer 5′-biotin-ATCCAGAGTGACGCAGCA 3 Reverse primer 5′-biotin-ACTAAGCCACCGTGTCCA 4 60-mer aptamer 5′-ATCCAGAGTGACGCAGCA-20N- 5 library TGGACACGGTGGCTTAGT 65-mer aptamer 5′-ATCCAGAGTGACGCAGCA-25N- 6 library TGGACACGGTGGCTTAGT 70-mer aptamer 5′-ATCCAGAGTGACGCAGCA-30N- 7 library TGGACACGGTGGCTTAGT 75-mer aptamer 5′-ATCCAGAGTGACGCAGCA-35N- 8 library TGGACACGGTGGCTTAGT 80-mer aptamer 5′-ATCCAGAGTGACGCAGCA-40N- 9 library TGGACACGGTGGCTTAGT

Twenty plasma samples from prostate cancer patients and twenty plasma samples from normal controls (non-prostate cancer) are used for selection. Aliquots of the libraries are incubated with each of the 40 samples. Microvesicles are recovered from each of the samples by affinity selection with an anti-tetraspanin antibody. Any aptamers bound to the microvesicles are eluted from the recovered microvesicles.

In a first set of experiments, the aptamer pools from each of the prostate cancer patients are pooled together. Each of the aptamer pools is sequenced using the Truseq next generation sequencing platform according to the manufacturer's instructions (Illumina Corporation). The aptamer pools from each of the controls patients are pooled together and the same steps are repeated to identify the sequences of the control aptamer candidates. The aptamers from each of the prostate cancer and control pools are compared using bioinformatics algorithms to identify aptamers that bind the microvesicles in the cancer samples but not the controls. The comparison is also used to identify aptamers that bind the microvesicles in the control samples but not the cancer samples.

In a second set of experiments, the aptamer pools that bound microvesicles from each different sample are sequenced individually using the Truseq next generation sequencing platform according to the manufacturer's instructions (Illumina Corporation). The aptamers from each of the prostate cancer and control pools are compared using bioinformatics algorithms to identify aptamers that bind the microvesicles in the cancer samples but not the controls. The comparison is also used to identify aptamers that bind the microvesicles in the control samples but not the cancer samples.

The experiments above provide subpools of aptamers that can be used in an affinity assay to distinguish microvesicles in prostate cancer (PCa) samples versus normal (non-PCa) samples. The pools of aptamer are further reduced in complexity by applying a number of filters. First, the stability of the aptamers is estimated using bioinformatics analysis. Aptamers with greater estimated stability are retained. Second, aptamers are grouped by projected secondary structure. See Example 4. A subset of aptamers from those having common estimated structures is retained. Finally, the remaining subset of aptamers is used as binding agents in an immunoassay to identify those aptamers that perform best to separate microvesicles from cancer and non-cancer samples.

Example 6 Strand Separation

After each round of selection in the Example above, the recovered aptamer pool was amplified using PCR with standard protocols. The PCR products were captured and strand separated using methodology presented in this Example.

Positive Selection Strand Separation

1. Aliquot each sample into a 1.7 ml Eppendorf tube.

2. Pre-aliquot into labeled tubes 5 μL 1M HCl. There should be one tube/sample.

3. If sample volume is ˜38 μL, add 420 μL, of 0.05% Tween in 1×PBS (to prepare add 250 μL of Tween into 500 mL of Hyclone PBS and mix well-pipet tween slowly-material is viscous).

4. Prepare streptavidin beads, 40 μL per sample is needed (keep beads pooled in a tube for washes). If performing 25 strand separations-aliquot 540 μL of beads×2 tubes (includes overage). Vortex beads well before preparing them, there should be no clumps evident.

5. Place beads on magnet and wait for the solution to clear.

6. Remove supernatant without disturbing the beads.

7. Add 1 mL 0.05% Tween in 1×PBS to the beads and mix off the magnet. Replace on the magnet after mixing and wait for the solution to clear.

8. Remove supernatant without disturbing the beads.

9. Repeat steps 7 and 8. Resuspend beads in tween-PBS solution in the same volume aliquoted previously

10. Vortex beads well off the magnet, and add 40 μL to each of the samples.

11. Cap the samples tightly and place on rotator for 15 minutes at room temperature.

12. Place samples back on the magnet to wash away unbound sample.

13. Add 1 mL 0.05% Tween in 1×PBS to each tube, aiming towards the magnetic wall. Wait for the solution to clear.

14. Remove supernatant without disturbing the beads.

15. Repeat steps 12 and 13. Make sure no remaining solution remains in the tube.

16. Off the magnet, add 50 μL of 0.1M NaOH to each sample.

17. Place tubes on Mix Mate for 5 minutes at 350 RPM room temperature.

18. After 5 minutes, place the tubes on the magnet.

19. After the beads clear and are stuck to the magnet, remove supernatant and add to appropriately labeled 5 μL HCl tubes (these should have been aliquoted and labeled prior to start of the strand separation). This should neutralize the solution. The solution should be slightly cloudy.

20. Bring the volume up to 100 μL in each tube by adding 45 μL of molecular grade RNase/DNase free water. Place samples briefly on ice.

21. Add 11 μL of 3M sodium acetate to each tube. This might clear some of the solution.

22. Add 350 μL of 95% ethanol to each tube.

23. Add 1.25 μL of glycogen to each tube, there should be a faint whitish trail that can be seen.

24. Mix by inversion 10×.

25. Centrifuge ethanol tubes for a minimum of 16 minutes at max speed at room temp.

26. When centrifugation is complete, remove ethanol from tubes, careful to not disturb the pellet. Use a p1000 first, followed up with a p200.

27. Let samples air dry for ˜5 minutes or until ethanol residue is gone. Do not let air dry too long.

28. Resuspend samples in 55 μL 25 mM HEPES in PBS-BN.

29. Let sit for ˜2 minutes and vortex sample and spin it down.

30. Aliquot 5 μl into tubes labeled with positive selection, the round number, date, sample number, and ‘post-Amp’. Freeze at −20° C.

31. The remaining 50 μL is used for the next round of selection.

Example 7 Aptamer Target Identification

The Examples above presents a method of identifying disease-specific aptamers. The Example further presents methods of identifying the targets of the disease-specific aptamers.

An aptamer is tethered to a microbead. The aptamer has shown the ability to preferentially recognize cancer vesicles versus controls. The microbead is incubated with a biological sample comprising cancer vesicles under conditions such that the aptamer can bind to the antigen it recognizes on the cancer microvesicle surface. Once the complex has formed, the aptamer is photo-crosslinked to the antigen. The vesicle is then disrupted using a surfactant, thereby leaving the aptamer-target complex tethered to the microbead. The microbeads are washed and recovered. The crosslinks are disrupted thereby releasing the target into solution. The beads are spun from solution and the target is further concentrated and isolated using size exclusion chromatography. The purified target is subjected to mass spectrometry for identification.

Example 8 Identification of Aptamers Specific to Cancer-derived Microvesicles

In this Example, an aptamer library is screened to identify aptamers that distinguish between microvesicles circulating in the blood of breast cancer patients and microvesicles circulating in the blood of healthy, control individuals (i.e., without breast cancer).

Microvesicles were isolated from plasma of a pool of 60 breast cancer patients (BrCa+). Microvesicles were also isolated from pool of 60 non-cancer samples (BrCa−). Microvesicles were isolated from the plasma using ultracentrifugation (120,000×g). Microvesicles were in the pellet from the ultracentrifugation. The supernatant from the ultracentrifugation was saved to use as a control. The microvesicles from both sample types were conjugated to MagPlex beads (Luminex Corp, Austin Tex.). Optionally, the isolated microvesicles are incubated with anti-HSA/IgG/Fibrinogen beads to remove these highly abundant blood proteins. However, the conjugation step can be optimized to favor conjugation of the microvesicles such that removal of highly abundant proteins is not strictly necessary.

The starting aptamer library is in Example 5 above. The aptamer library is incubated with either the cancer or control microvesicle-conjugated beads as described below:

Positive Selection Against Microvesicle Coated Magnetic Beads

Abbreviations: TK—Transcription; NTC—No template control.

Steps:

-   -   1. ^(1st) Round: Mix 1 nmol purified input aptamer library with         20 μl of resuspended beads (conjugated with microvesicle). 10 uL         of 10×PBS+1% BSA, 3 μl 100 mM MgCl₂, and 47 uL H₂O. This gives a         final concentration of 1×PBS, 0.1% BSA, 3 mM MgCl₂.         -   1.1 The addition of MgCl₂ in this step gives a concentration             of 3 mM MgCl₂. This is the binding concentration for the             entire process.         -   1.2 Following Rounds: Mix 20 μl of transcription product (15             mM MgCl₂ inside) with 20 μl of washed microvesicle coated             beads, plus 9 uL 10×PBS with 1% BSA, 51 uL H₂O. No             additional MgCl₂ is needed because the MgCl₂ in the diluted             transcription product (TK) provides a final concentration of             3 mM MgCl₂.     -   2. Incubate for 30 min at 37° C., shake at 1000 rpm, and pipet         mix every 10 minutes.     -   3. Wash the beads:         -   3.1 One washing cycle comprises:             -   3.1.1 Remove the beads from the magnet             -   3.1.2 Resuspend beads in 100 μl 1×PBS+3 mM MgCl₂ off the                 magnet.             -   3.1.3 Incubate sample for 30 seconds off of the magnet.             -   3.1.4 Place the sample back onto the magnet, and wait                 until the beads are on the side.             -   3.1.5 Remove and discard the supernatant.             -   3.1.6 Resuspend in 100 μl 1×PBS+3 mM MgCl₂+0.1% BSA off                 of the magnet.             -   3.1.7 Incubate sample for 3 minutes off of the magnet.             -   3.1.8 Place the sample back onto the magnet, and wait                 until the beads are on the side.             -   3.1.9 Remove and discard the supernatant         -   3.2 ^(1st) Round: Place bead mixture on a magnet and remove             the supernatant. Wash once with 100 μl 1×PBS+3 mM MgCl₂+0.1%             BSA (by pipette mixing the beads), and discard buffer.         -   3.3 Following Rounds: Increase the washing steps every             second round by one more washing step up to 3 washing steps.     -   4. Add 55 μl MilliQ water to the bead sample.     -   5. Elute the retained aptamers by incubating the bead sample for         5 min at 80° C.         -   5.1 Check if there is 50 if not spin the sample down to spin             down the condensed water off the top.         -   5.2 Transfer the supernatant to a new vial. Work quickly to             avoid the strands rebinding the beads.             -   5.2.1 Use 50 μl eluate for downstream steps (e.g.,                 RT-PCR) and store the rest at −20° C.

The aptamers retained from the above positive selection are sequenced using Next Generation sequencing technology consisting of Ion Torrent NGS (Life Technologies, Inc., Carlsbad, Calif.). The MiSeq system may be used also (Illumina, Inc., San Diego, Calif.). The sequences are compared to identify aptamers that are found in the cancer samples and not the control samples, and vice versa. Such aptamers provide candidates that can be used to distinguish between BrCa and non-BrCa samples. See FIG. 2A-C and related discussion above for further details. See Example 9 below for use of selected aptamers to detect microvesicles.

Example 9 Detection of Cancer-Derived Microvesicles Using Aptamers

Aptamers of the invention, e.g., as identified in Example 8 above, can be used as binding agents to detect a biomarker. In this Example, aptamers are used as binding agents to detect cancer-derived microvesicles and microvesicle surface antigens.

FIGS. 3A-3D illustrate the use of an anti-EpCAM aptamer (Aptamer 4; SEQ ID NO. 10) to detect a microvesicle population in plasma samples. Plasma samples were obtained from three men with prostate cancer and three men without prostate cancer (referred to as controls or normals). Antibodies to the following microvesicle surface protein antigens of interest were conjugated to microbeads (Luminex Corp, Austin, Tex.): A) EGFR (epidermal growth factor receptor); B) PBP (prostatic binding protein; also known as PEBP1 (phosphatidylethanolamine binding protein 1)); C) EpCAM (epithelial cell adhesion molecule); and D) KLK2 (kallikrein-related peptidase 2). Microvesicles in the plasma samples were captured using the bead-conjugated antibodies. Fluorescently labeled Aptamer 4 was used as a detector in the microbead assay. FIGS. 3A-3D show the average median fluorescence values (MFI values) detected for the bead-captured and Aptamer 4 detected microvesicles. Each plot individually shows the three cancer (C1-C3) and three normal samples (N1-N3). These data show that, on average, the prostate cancer samples have higher levels of microvesicles containing the target proteins than the normals.

FIGS. 4A-B show binding of the indicated aptamers BCE8 (Panel A; SEQ ID NO. 11) and BCE11 (Panel B; SEQ ID NO. 12) against microbeads conjugated to various input samples. The input sample is indicated on the X axis from left to right as follows: 1) Cancer Exosome: aptamer binding to microbeads conjugated to microvesicles isolated from plasma samples from breast cancer patients; 2) Cancer Non-exosome: aptamer binding to microbeads conjugated to plasma samples from breast cancer patients after removal of microvesicles by ultracentrifugation; 3) Non-Cancer Exosome: aptamer binding to microbeads conjugated to microvesicles isolated from plasma samples from normal (i.e., non-breast cancer) patients; 4) Non-Cancer Non-Exosome: aptamer binding to microbeads conjugated to plasma samples from breast cancer patients after removal of microvesicles by ultracentrifugation. As shown in FIGS. 4A-B, the aptamers were each able to distinguish between the cancer microvesicle samples versus the supernatant control samples and the non-cancer microvesicles.

Example 10 Disease Diagnosis

This Example illustrates the use of the aptamers of the invention to diagnose a proliferative disease such as a cancer.

A suitable quantity of an aptamer that binds a cancer-derived microvesicle is synthesized via chemical means known in the art. The aptamers are conjugated to a diagnostic agent suitable for detection, such as a fluorescent moiety, using a conjugation method known in the art.

The composition is applied to microvesicles isolated from blood samples taken from a test cohort of patients suffering from a proliferative disease associated with the overexpression of microvesicles, e.g., prostate, breast, or lung cancer. The composition is likewise applied to microvesicles isolated from blood samples taken from a negative control cohort, not suffering from a proliferative disease.

The use of appropriate detection techniques (e.g., microbead assay or flow cytometry) on the test cohort samples indicates the presence of disease, while the same techniques applied to the control cohort samples indicate the absence of disease.

The results show that the aptamers of the invention are useful in diagnosing proliferative diseases.

While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby. 

1. A method of identifying at least one aptamer comprising: (a) providing a pool of candidate aptamers; (b) contacting a first at least one biological sample with the pool provided in step (a), wherein the first at least one biological sample comprises a microvesicle population; (c) identifying a first subpool of candidate aptamers that bound at least one microvesicle in the first at least one biological sample in step (b); (d) contacting a second at least one biological sample with the pool provided in step (a), wherein the second at least one biological sample comprises a microvesicle population; (e) identifying a second subpool of candidate aptamers that bound at least one microvesicle in the second at least one biological sample in step (d); and (f) comparing the members of the first and second subpools of candidate aptamers to identify at least one member of a pool that is overrepresented in one of the subpools versus the other subpool, thereby identifying the at least one aptamer.
 2. (canceled)
 3. The method of claim 1, wherein each of the first at least one biological samples are separately contacted with aliquots of the pool in step (b).
 4. The method of claim 1, wherein each of the second at least one biological samples are separately contacted with aliquots of the pool in step (d).
 5. (canceled)
 6. The method of claim 1, further comprising repeating steps (b)-(c) at least 1 time prior to step (f), wherein the first subpool of candidate aptamers from step (c) is used as the starting pool of candidate aptamers when repeating step (b).
 7. The method of claim 1, further comprising repeating steps (d)-(e) at least 1 time prior to step (f), wherein the second subpool of candidate aptamers from step (e) is used as the starting pool of candidate aptamers when repeating step (d).
 8. The method of claim 1, further comprising repeating steps (a)-(f) at least 1 time, wherein the identified one or more aptamer from step (f) is used as the starting pool of candidate aptamers when repeating step (a).
 9. The method of claim 1, wherein the first at least one biological sample comprises a diseased sample.
 10. The method of claim 9, wherein each of the first at least one biological samples comprises a sample representative of a same disease.
 11. The method of claim 9, wherein the second at least one biological sample comprises a non-diseased sample.
 12. The method of claim 9, wherein the first at least one biological sample comprises a same disease as the second at least one biological sample, and wherein the disease in the first and second samples differs in at least one of clinical stage, pathologic stage, aggressiveness, growth rate, receptor status, prior treatment, response to a same to treatment, and response to different treatments.
 13. The method of claim 9, wherein the disease comprises a cancer.
 14. The method of claim 13, wherein the cancer comprises a prostate cancer, a lung cancer, a breast cancer, a brain cancer, an ovarian cancer, a colorectal cancer, or a melanoma.
 15. The method of claim 1, wherein the first at least one biological sample and the second at least one biological sample comprise bodily fluids.
 16. (canceled)
 17. The method of claim 15, wherein the bodily fluid comprises peripheral blood, sera, plasma, ascites, urine, cerebrospinal fluid (CSF), sputum, saliva, bone marrow, synovial fluid, aqueous humor, amniotic fluid, cerumen, breast milk, broncheoalveolar lavage fluid, semen, prostatic fluid, cowper's fluid or pre-ejaculatory fluid, female ejaculate, sweat, fecal matter, tears, cyst fluid, pleural and peritoneal fluid, pericardial fluid, lymph, chyme, chyle, bile, interstitial fluid, menses, pus, sebum, vomit, vaginal secretions, mucosal secretion, stool water, pancreatic juice, lavage fluids from sinus cavities, bronchopulmonary aspirates, blastocyl cavity fluid, umbilical cord blood, or a derivative of any thereof.
 18. The method of claim 15, wherein the bodily fluid comprises peripheral blood, plasma, serum or a derivative of any thereof.
 19. The method of claim 1, wherein the biological sample comprises a tissue sample or cell culture sample.
 20. The method of claim 1, wherein the identifying in step (c) and/or step (e) comprises sequencing the candidate aptamers that bound the at least one microvesicle.
 21. The method of claim 20, wherein comparing the members of the first and second subpools in step (f) comprises comparing the sequences of the aptamers identified in step (c) and/or step (e).
 22. (canceled)
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 24. (canceled)
 25. The method of claim 1, further comprising filtering the identified at least one aptamer.
 26. The method of claim 25, wherein filtering the identified at least one aptamer comprises calculating a stability of the at least one aptamer, identifying a secondary structure of the at least one aptamer, and/or separately contacting each of the at least one aptamer with a biological sample.
 27. (canceled)
 28. (canceled)
 29. (canceled)
 30. (canceled)
 31. (canceled)
 32. (canceled)
 33. (canceled) 